Methods and systems for interactive goal setting and recommender using events having combined activity and location information

ABSTRACT

A method for generating recommendations for achieving goals is described. The method includes receiving a goal for a user account. The goal is associated with an activity that is trackable via a monitoring device. The method further includes receiving tracking data associated with the monitoring device. At least part of the tracking data is associated to the activity. The method includes receiving geo-location data associated with the monitoring device. The geo-location data is correlated to the tracking data. The method includes analyzing the received tracking data and geo-location data to characterize a current performance metric for the activity and generating a recommendation for the user account. The recommendation identifies the current performance metric and a suggested action and location for increasing the current performance metric to achieve the goal.

CLAIM OF PRIORITY

This application is a continuation of U.S. patent application Ser. No.14/059,919, filed on Oct. 22, 2013, titled “Methods and Systems forInteractive Goal Setting and Recommender Using Events Having CombinedActivity and Location Information”, which is incorporated by referenceherein in its entirety

This application Ser. No. 14/059,919 is a continuation of U.S. patentapplication Ser. No. 13/959,720, filed on Aug. 5, 2013, titled “Methodsand Systems for Interactive Goal Setting and Recommender Using EventsHaving Combined Activity and Location Information”, now U.S. Pat. No.8,620,617, which is incorporated by reference herein in its entirety.

The application Ser. No. 13/959,720 claims the benefit of and priority,under 35 U.S.C. 119§(e), to a Provisional Patent Application No.61/680,230, filed on Aug. 6, 2012, and entitled “GPS ENABLED ACTIVITYAND SLEEP TRACKER,” which is incorporated by reference herein in itsentirety.

The application Ser. No. 13/959,720 is a continuation-in-part of U.S.patent application Ser. No. 13/693,334, filed on Dec. 4, 2012, titled“Portable Monitoring Devices and Methods for Operating Same”, now U.S.Pat. No. 8,548,770, which is a divisional of U.S. patent applicationSer. No. 13/667,229, filed on Nov. 2, 2012, titled “Portable MonitoringDevices and Methods for Operating Same”, now U.S. Pat. No. 8,437,980,which is a divisional of U.S. patent application Ser. No. 13/469,027,now U.S. Pat. No. 8,311,769, filed on May 10, 2012, titled “PortableMonitoring Devices and Methods for Operating Same”, which is adivisional of U.S. patent application Ser. No. 13/246,843, now U.S. Pat.No. 8,180,591, filed on Sep. 27, 2011, which is a divisional of U.S.patent application Ser. No. 13/156,304, filed on Jun. 8, 2011, titled“Portable Monitoring Devices and Methods for Operating Same”, whichclaims the benefit of and priority to, under 35 U.S.C. 119§(e), to U.S.Provisional Patent Application No. 61/388,595, filed on Sep. 30, 2010,and titled “Portable Monitoring Devices and Methods for Operating Same”and to U.S. Provisional Patent Application No. 61/390,811, filed on Oct.7, 2010, and titled “Portable Monitoring Devices and Methods forOperating Same”, all of which are hereby incorporated by reference intheir entirety.

The application Ser. No. 13/959,720 is a continuation-in-part of U.S.patent application Ser. No. 13/759,485, filed on Feb. 5, 2013, titled“Portable Monitoring Devices and Methods for Operating Same”, now U.S.Pat. No. 8,543,351, which is a divisional of U.S. patent applicationSer. No. 13/667,229, filed on Nov. 2, 2012, titled “Portable MonitoringDevices and Methods for Operating Same”, now U.S. Pat. No. 8,437,980,which is a divisional of U.S. patent application Ser. No. 13/469,027,now U.S. Pat. No. 8,311,769, filed on May 10, 2012, titled “PortableMonitoring Devices and Methods for Operating Same”, which is adivisional of U.S. patent application Ser. No. 13/246,843, now U.S. Pat.No. 8,180,591, filed on Sep. 27, 2011, which is a divisional of U.S.patent application Ser. No. 13/156,304, filed on Jun. 8, 2011, titled“Portable Monitoring Devices and Methods for Operating Same”, whichclaims the benefit of and priority to, under 35 U.S.C. 119§(e), to U.S.Provisional Patent Application No. 61/388,595, filed on Sep. 30, 2010,and titled “Portable Monitoring Devices and Methods for Operating Same”and to U.S. Provisional Patent Application No. 61/390,811, filed on Oct.7, 2010, and titled “Portable Monitoring Devices and Methods forOperating Same”, all of which are hereby incorporated by reference intheir entirety.

FIELD

The present disclosure relates to systems and methods for capturingactivity data over a period of time and associating the capturedactivity data into identification of locations of a user performingactivities.

BACKGROUND

In recent years, the need for health and fitness has grown tremendously.The growth has occurred due to a better understanding of the benefits ofgood fitness to overall health and wellness. Unfortunately, althoughtoday's modern culture has brought about many new technologies, such asthe Internet, connected devices and computers, people have become lessactive. Additionally, many office jobs require people to sit in front ofcomputer screens for long periods of time, which further reduces aperson's activity levels. Furthermore, much to today's entertainmentoptions involve viewing multimedia content, computer social networking,and other types of computer involved interfacing. Although such computeractivity can be very productive as well as entertaining, such activitytends to reduce a person's overall physical activity.

To provide users concerned with health and fitness a way of measuring oraccounting for their activity or lack thereof, fitness tracker are oftenused. Fitness trackers are used to measure activity, such as walking,motion, running, sleeping, being inactive, bicycling, exercising on anelliptical trainer, and the like. Usually, the data collected by suchfitness trackers can be transferred and viewed on a computing device.However, such data is often provided as a basic accumulation of activitydata.

It is in this context that embodiments described herein arise.

SUMMARY

Embodiments described in the present disclosure provide systems,apparatus, computer readable media, and methods for segmenting a periodof time into identification of locations of a user performingactivities. This segmentation provides a way of identifying particularactivities to particular locations. Using the segmentations, the systemsand methods can identify one or more events that may have occurredduring the period of time of activity. In one embodiment, the events canbe displayed on a screen of a device, and a user is able tointeractively view data concerning the events with contextualinformation, e.g., where certain events occurred.

In one embodiment, as described below, the events are automaticallyassociated with locations, and the locations can be associated withcontextual information concerning the locations. For instance, if atracking device detects certain activity at a particular location (e.g.,a map location), the mapping data or related databases can be queried todetermine that the map location corresponds to a golf course. The systemcan then generate information that is graphically presented to the user,concerning the particular tracked activity as corresponding to golfing.In some embodiments, the locations can be identified over time, e.g., byreceived user feedback (e.g., this is my home, this is a coffee shop,this is my work).

In some embodiments, the locations can be inferred or learned based onthe activities and times of day, and/or repeat activities over a periodof time (e.g., based on an identifiable pattern). For example, if theuser/tracker is typically experiencing low activity from 9:00 am and11:55 am, Monday-Friday, it can be inferred using a rules database andlearning logic that the user is at work or is working. In anotherembodiment, the user can be asked, “are you at work?” via a computingdevice or a tracking device, and based on the user's response, databasecan associate particular locations (e.g., geo-location) to particularactual location (e.g., work), and collect the activity data forpresentation along with the most appropriate location.

In some embodiments, an activity that is performed by a user is inferredbased on geo-locations of a monitoring device or a computing device usedby the user. For example, a processor of the monitoring device, of thecomputing device, of a server, or of a virtual machine determines basedon the geo-locations that a user is at a location, e.g., a gym, home,work, etc. The processor retrieves from an activity-location databaseone or more activities that may be performed by the user at thelocation. For example, the activity-location database indicates that theuser may be performing one or more activities, e.g., using a treadmill,using an elliptical trainer, lifting weights to build resistance,swimming laps, etc., while at a gym. As another example, theactivity-location database indicates that the user may be performing oneor more activities, e.g., walking, climbing stairs, descending stairs,sleeping, etc., while at home. The processor retrieves one or more ofthe activities from the activity-location database that correspond tothe location and determines that the user is performing one or more ofthe activities.

Broadly speaking, the systems and methods facilitate determination of anactivity level of an activity performed by a user at a location. Forexample, the systems and methods can determine that the user issedentary for a particular period of time when the user is at work. Asanother example, the systems and methods can determine that the user isactive when the user is at home. The activity or lack of activity istherefore contextually associated to a particular location. The systemsand methods determine activity levels of one or more activitiesperformed by the user during a period of time. The user can view theactivity levels of an activity performed at a location and decidewhether to perform a different activity at the location, to perform anactivity at another location, or to continue performing the activitywhen at the location. By providing the user location context toactivities, the user is able to better view his or her actual activityperformance and better health decisions can be made regarding and/oradjustments can be made in lifestyle. For instance, a user may find thatwalking to the train station can significantly increase a person'sactivity, over taking a bus to the train. These simple decisions inactivity can act to significantly improve a person's health, butproviding context as to what and where activity is taking place canprovide better understanding as to how simple changes can have largeimpacts in overall fitness.

In some embodiments, a method for generating recommendations forachieving goals is described. The method includes receiving a goal for auser account. The goal is associated with an activity that is trackablevia a monitoring device. The method further includes receiving trackingdata associated with the monitoring device. At least part of thetracking data is associated to the activity. The method includesreceiving geo-location data associated with the monitoring device. Thegeo-location data is correlated to the tracking data. The methodincludes analyzing the received tracking data and geo-location data tocharacterize a current performance metric for the activity andgenerating a recommendation for the user account. The recommendationidentifies the current performance metric and a suggested action andlocation for increasing the current performance metric to achieve thegoal.

In various embodiments, a method for generating recommendations forachieving goals is described. The method includes receiving a goal for auser account. The goal is associated with an activity that is trackablevia a monitoring device. The method further includes obtaining trackingdata associated with the monitoring device. At least part of thetracking data is associated to the activity. The method includesobtaining geo-location data associated with the monitoring device. Thegeo-location data is correlated to the tracking data. The methodincludes analyzing the received tracking data and geo-location data tocharacterize a current performance metric for the activity andgenerating a recommendation for the user account. The recommendationidentifies the current performance metric and a suggested action andlocation for increasing the current performance metric to achieve thegoal.

In several embodiments, a method includes receiving a goal associatedwith a first activity of a user and a first location of a monitoringdevice. The first activity is performed when the user is using themonitoring device. The first location is determined when the user isusing the monitoring device. The method further includes determiningwhether a milestone to achieve the goal is reached. The operation ofdetermining whether the milestone is reached is based on an amount ofthe first activity performed by the user over a period of time. Themethod includes recommending a second location to be visited by the userand an amount of a second activity to be performed by the user toachieve the milestone upon determining that the milestone will not bereached.

In various embodiments, a method includes receiving a goal associatedwith a first activity of a user and a first location of a monitoringdevice. The first activity is performed when the user is using themonitoring device. The first location is determined when the user isusing the monitoring device. The method includes determining whether thegoal has a reduced likelihood of being completed. The operation ofdetermining whether the goal has the reduced likelihood is based on anamount of the first activity performed by the user. The method includesrecommending a second location to be visited by the user to achieve thegoal upon determining that the goal has the reduced likelihood of beingcompleted.

Other aspects will become apparent from the following detaileddescription, taken in conjunction with the accompanying drawings,illustrating by way of example the principles of embodiments describedin the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments described in the present disclosure may best beunderstood by reference to the following description taken inconjunction with the accompanying drawings in which:

FIG. 1A illustrates a variety of situations in which a system forsegmenting a period of time into identification of locations of a userperforming activities is used, in accordance with one embodimentdescribed in the present disclosure.

FIG. 1B is a diagram of a method for determining an amount of a type ofmovement of a monitoring device over a period of time, in accordancewith one embodiment described in the present disclosure.

FIG. 1C is a diagram of a method for determining an amount of anothertype movement of a monitoring device over a period of time, inaccordance with one embodiment described in the present disclosure.

FIG. 1D is a diagram of a method for determining an amount of yetanother type movement of a monitoring device over a period of time, inaccordance with one embodiment described in the present disclosure.

FIG. 1E is a diagram of a method for determining an amount of anothertype movement of a monitoring device over a period of time, inaccordance with one embodiment described in the present disclosure.

FIG. 2A is a diagram of a system for transferring data between amonitoring device and a server via a computing device and a network, inaccordance with one embodiment described in the present disclosure.

FIG. 2B is a diagram of an embodiment of a system for transferring databetween a monitoring device and the server via a mobile computing deviceand the network, in accordance with one embodiment described in thepresent disclosure.

FIG. 3A is a diagram of a system to illustrate components of amonitoring device, in accordance with one embodiment described in thepresent disclosure.

FIG. 3B is a diagram of a system to illustrate components of anothermonitoring device, in accordance with one embodiment described in thepresent disclosure.

FIG. 4A is an isometric view of a monitoring device that is worn arounda hand of a user or around a leg of the user, in accordance with oneembodiment described in the present disclosure.

FIG. 4B is an isometric view of another monitoring device that fits toan article of clothing or a belt worn by a user, in accordance with oneembodiment described in the present disclosure.

FIG. 4C is a view of yet another monitoring device that fits to anarticle of clothing or a belt worn by a user, in accordance with oneembodiment described in the present disclosure.

FIG. 4D is an isometric view of another monitoring device that fits toan arm of a user, in accordance with one embodiment described in thepresent disclosure.

FIG. 5 is a block diagram of a computing device, in accordance with oneembodiment described in the present disclosure.

FIG. 6A is a flowchart of a method for segmenting a period of time intoidentification of locations of a user performing activities, inaccordance with one embodiment described in the present disclosure.

FIG. 6B is a flowchart of another method for segmenting a period of timeinto identification of locations of a user performing activities, inaccordance with one embodiment described in the present disclosure.

FIG. 6C is a flowchart of yet another method for segmenting a period oftime into identification of locations of a user performing activities,in accordance with one embodiment described in the present disclosure.

FIG. 6D is a flowchart of a method for segmenting a period of time intoidentification of locations of a user performing activities, inaccordance with one embodiment described in the present disclosure.

FIG. 6E is a flowchart of another method for segmenting a period of timeinto identification of locations of a user performing activities, inaccordance with one embodiment described in the present disclosure.

FIG. 6F is a flowchart of a method for combining a map with event data,in accordance with one embodiment described in the present disclosure.

FIG. 7A is a graphical user interface (GUI) that displays one or moreevents and that is generated by executing the method of FIG. 6A, 6B, 6C,6E, or 6F, in accordance with one embodiment described in the presentdisclosure.

FIG. 7B is a diagram of another GUI that displays one or more events andthat is generated by executing the method of FIG. 6A, 6B, 6C, 6E, or 6Fin accordance with one embodiment described in the present disclosure.

FIG. 7C is a diagram illustrating a method for establishing boundariesbetween two locations arrived at by a user over one or more periods oftime, in accordance with one embodiment described in the presentdisclosure.

FIG. 7D is a diagram of a GUI to illustrate a method of allowing a userto choose a location in case of common geo-locations between multiplelocations, in accordance with one embodiment described in the presentdisclosure.

FIG. 7E is a diagram of a web page that includes a GUI that displays oneor more events and that is generated by executing the method of FIG. 6A,6B, 6C, 6E, or 6F, in accordance with one embodiment described in thepresent disclosure.

FIG. 7F-1 is a GUI to illustrate activity levels of one or activitiesperformed by a user over a period of time and to illustrate activitylevels associated with one or more locations at which the activities areperformed, in accordance with one embodiment described in the presentdisclosure.

FIG. 7F-2 is a zoom-in of the GUI of FIG. 7F-1, in accordance with oneembodiment described in the present disclosure.

FIG. 7G-1 is a diagram of a first portion of a daily journal GUI thatincludes one or more GUIs that include event data for periods of time,in accordance with one embodiment described in the present disclosure.

FIG. 7G-2 is a diagram of a second portion of the daily journal GUI, inaccordance with one embodiment described in the present disclosure.

FIG. 7G-3 is a diagram of a third portion of the daily journal GUI, inaccordance with one embodiment described in the present disclosure.

FIG. 7H is a diagram of another daily journal GUI that includes one ormore GUIs that include event data for periods of time, in accordancewith one embodiment described in the present disclosure.

FIG. 7I is a GUI that provides an overview of one or more levels of oneor more activities performed by a user at one or more locations over aperiod of time, in accordance with one embodiment described in thepresent disclosure.

FIG. 7J is a diagram of a GUI that includes a detailed view ofactivities displayed in the GUI of FIG. 7I, in accordance with oneembodiment described in the present disclosure.

FIG. 7K is a diagram of a GUI that includes a more detailed view ofactivities displayed in the GUI of FIG. 7J, in accordance with oneembodiment described in the present disclosure.

FIG. 7L is a diagram illustrating a method of combining activity levelsover a period of time, in accordance with one embodiment described inthe present disclosure.

FIG. 7M is a diagram of a GUI that describes an aggregate level of oneor more activities performed by a user over a period of time, inaccordance with one embodiment described in the present disclosure.

FIG. 7N is a diagram of a pie-chart of locations at which a userperforms one or more activities and of percentages of activity levels atone or more locations over a period of time, in accordance with oneembodiment described in the present disclosure.

FIG. 7O is a diagram of a GUI that includes an overlay of a map on oneor more locations that a user visits during a period of time to performone or more activities performed by the user during a period of time, inaccordance with one embodiment described in the present disclosure.

FIG. 7P is a diagram of a web page that illustrates that a map isoverlaid on an event region to indicate a geo-location of a user at atime within a time period in which the user performs one or moreactivities, in accordance with one embodiment described in the presentdisclosure.

FIG. 7Q is a diagram of a GUI that includes a map below an event region,in accordance with one embodiment described in the present disclosure.

FIG. 7R is a diagram of a web page that is used to illustrate an overlayof event data on a map, in accordance with one embodiment described inthe present disclosure.

FIG. 7S is a diagram of a web page that is used to illustrate a zoom-inof a portion of the map of FIG. 7R and of activity data of an activityperformed by a user while the user is at the portion, in accordance withone embodiment described in the present disclosure.

FIG. 7T is a diagram of an embodiment of a web page that includes a GUIthat further includes an overlay of a map on a user's path, inaccordance with one embodiment described in the present disclosure.

FIG. 7U is a diagram of an embodiment of the web page of FIG. 7T toillustrate a zoom-in of a portion of the map of FIG. 7T and toillustrate activity data associated with the zoom-in, in accordance withone embodiment described in the present disclosure.

FIG. 7V is a diagram of an embodiment of a GUI that includes furtherdetails regarding the user's path of FIG. 7T, in accordance with oneembodiment described in the present disclosure.

FIG. 8 is a diagram of one or more location identifiers and one or moreactivity identifiers, in accordance with one embodiment described in thepresent disclosure.

FIG. 9A is a flowchart of a method for generating a recommendation tohelp a user achieve a goal, in accordance with one embodiment describedin the present disclosure.

FIG. 9B is a flowchart of another method for generating a recommendationto help a user achieve a goal, in accordance with one embodimentdescribed in the present disclosure.

FIG. 10A is a flowchart of a method for recommending a location or anactivity to a user to achieve a milestone, in accordance with oneembodiment described in the present disclosure.

FIG. 10B is a diagram of a flowchart of another method for recommendinga location or an activity to a user to achieve a milestone, inaccordance with one embodiment described in the present disclosure.

FIG. 10C is a flowchart of a method for recommending a location or anactivity to a user to achieve a goal, in accordance with one embodimentdescribed in the present disclosure.

FIG. 10D is a flowchart of another method for recommending a location oran activity to a user to achieve a goal, in accordance with oneembodiment described in the present disclosure.

FIG. 11A is a diagram of a GUI for illustrating use of one or moremilestones to achieve a goal and a recommendation to achieve amilestone, in accordance with one embodiment described in the presentdisclosure.

FIG. 11B is a diagram of a GUI to illustrate provision of acomputer-generated award to a user account when a milestone is achieved,in accordance with one embodiment described in the present disclosure.

FIG. 11C is a diagram of a GUI to illustrate a recommendation to achievea milestone, in accordance with one embodiment described in the presentdisclosure.

FIG. 11D is a diagram of a GUI to illustrate that a user may perform adifferent activity at a location than that performed by the user so asto allow the user to achieve a milestone, in accordance with oneembodiment described in the present disclosure.

FIG. 12 is a diagram of a web page to illustrate that a user may achievea milestone by visiting a location that is close to another location ofthe user and performing an activity at the location to be visited, inaccordance with one embodiment described in the present disclosure.

FIG. 13 is a diagram of a GUI that illustrates a recommendation ofperforming a different activity at the same location, in accordance withone embodiment described in the present disclosure.

FIG. 14 is a diagram of a calendar GUI and another calendar GUI toillustrate a recommendation to achieve a goal and to illustrateachievement of the goal by a user, in accordance with one embodimentdescribed in the present disclosure.

FIG. 15 is a diagram illustrating a recommendation to achieve amilestone, in accordance with one embodiment described in the presentdisclosure.

FIG. 16 is a diagram of a GUI that includes a recommendation made by anadvertiser, in accordance with one embodiment described in the presentdisclosure.

FIG. 17 is a diagram of an embodiment of a GUI that is presented to auser to receive demographic data regarding the user from the user, inaccordance with one embodiment described in the present disclosure.

DETAILED DESCRIPTION

Embodiments described in the present disclosure provide systems,apparatus, computer readable media, and methods for analyzing trackedactivity data and segmenting/associating the activity data tocontextually identifiable locations where a user, wearing an activitytracker performed such activities. This segmentation provides a way ofidentifying events that associate the identified activities toparticular locations. In one embodiment, the data is collected from anactivity tracker and then transferred to a computing device. In someembodiments, the computing device can include a portable device, such asa smart phone, an internet connected watch, a tablet, a laptop, adesktop, etc. The computing device can then transfer the collectedactivity data to a server that is connected to the internet forprocessing.

In one embodiment, the term location refers to a geographic position.The geographic position can be identified on a map, identified on acoordinate identifier using global positioning data (e.g., GPS),identified using radio signal tower locator data (e.g., cell towers),identified using wireless internet router signal data (e.g., Wi-Fisignals), identified using router signal data for multi-flooridentification (e.g., floor-to-floor locator data), or combinationsthereof. In some embodiments, changes in location data includedetermining a difference between location identified data at varioustimes (e.g., every minute, every few minutes, every half hour, everyhour, at particular hour intervals or days). In some embodiments, thetime at which location data is obtained can vary depending on sensedactivity. For example, if less activity or motion is detected, fewerlocation data points need be taken.

The server can include one or more servers, which define a cloudprocessing system. The cloud processing system includes logic, code,programs and/or software for processing the activity data to produce theidentifiable events. The cloud processing system can provide a systemfor creating user accounts for users and their activity trackers. Theuser accounts enable users to view graphical users interfaces (GUIs)that render and display the events identified using the tracked activitydata and the location data (e.g., geo-location data). Processing logicon the servers associated with the cloud processing system can processthe tracked data, can access other Internet services (e.g., mappingservices, social networking services, location context services, etc.,to enable formulation or identification of a location for particularactivities, which define an event). Broadly speaking, an event isdefined to include a location and an activity.

In one embodiment, the events can be displayed on a screen of a device,and a user is able to interactively view data concerning the events withcontextual information, e.g., where certain events occurred.

In some embodiments, locations can be automatically identified byaccessing mapping services and other online databases that identifylocations. The online databases can include mapping programs, data fromsocial networks, tagged data, crowd-sourced data, etc.

In some embodiments, the locations can be inferred or learned based onthe activities and times of day, and/or repeat activities over a periodof time (e.g., based on an identifiable pattern). Databases of rules areconstructed and such rules are refined over time. The rules are used toenable the system to infer locations and provide appropriate contextualidentification to the locations. In some embodiments, the rules canshape themselves using learning systems, and can be tailored forspecific users. In still other embodiments, learned patterns andbehaviors of other users can be used to collaboratively identify rules,shape rules or determine locations or identify locations. For instance,if multiple users tag a location as a coffee bar, this information canbe used to associate “coffee bar” to some range of geo-location. If overtime, the location starts to get tagged as a breakfast bar, the rulescan be adjusted to now associate that geo-location as “breakfast bar.”As businesses or location contexts change over time, so can the rules.

In various embodiments, the shape rules are used to associate one ormore geo-locations with a location. For example, a shape, e.g., acircle, a polygon, an oval, a square, etc., is used to identify alocation on a graphical user interface. The graphical user interface mayinclude event data, a route, a map, or a combination thereof. A userchanges a size via a user interface of a monitoring device or via aninput device of a computing device of a shape to change a number ofgeo-locations associated with the location. For example, a userincreases a size of a circle to include more geo-locations within alocation that is identified by the circle. As another example, a userdecreases a size of a polygon to exclude a number of geo-locations fromwithin a location that is identified by the polygon. As another example,a center of a shape is changed to associate a different set ofgeo-locations with a location than that already associated with thelocation. For example, a user drags via a user interface of a monitoringdevice or via an input device of a computing device a point associatedwith, e.g., a center of, a vertex of, etc., a shape to a different spoton a graphical user interface. When the point is dragged, the shape isalso dragged to the difference spot and is associated with a differenceset of geo-locations than that before the movement of the center. Thegraphical user interface may include event data, a route, a map, or acombination thereof.

In another embodiment, the user may be allowed to post details ofparticular locations. The user can identify locations with particularcustom identifiers, e.g., “mom's house” or can select from predefinedidentifiers. In still other embodiments, the user can be asked toidentify a location. In still another embodiment, the user can be askedvia custom queries, such as: “Are you at work?”; “Is this your home?”;“Are you driving?”; “Do you need medical assistance? if so, say or typehelp” etc. Or, the queries can be presented to the user at a later time,such as when the user is viewing his or her past activity on a GUI. Insome embodiments, the queries can be provided via a cloud program, whenaccessing a computer with cloud access, via push notifications, viavoice requests, etc. Based on this returned feedback, the servers anddatabases of the cloud service can learn or associate locationidentification to particular locations, which are later identified bydetecting the geo-location of the tracker.

In some embodiments, a user tags a location as being associated with aperson known to the user. For example, a user logs into his/her useraccount and tags a location as being Mom's house, Eric's house,Jessica's house, Buddy's gym, etc. Examples of a person known to theuser include a friend of the user, a work mate of the user, a specialinterest of the user, a relative of the user, an acquaintance of theuser, or a family member of the user. The user tags via an input deviceof a computing device or via a user interface of a monitoring device. Aprocessor, e.g., a processor of the monitoring device, a processor ofthe computing device, a processor of a server, a processor of a virtualmachine, or a combination thereof, etc., determines that the tagindicates that the user knows the person. For example, the term “Mom”indicates that the person is a mom of the user. As another example,“Eric” indicates that the person is a friend, a relative, or anacquaintance of the user. The processor determines whether the persontagged has a user account. The user account is used to display eventdata that includes activities performed by the person and/or locationsvisited by the person while performing the activities, etc. Theprocessor suggests to the user to add the person to a social group, e.g.a friend group, a work mate group, a special interest group, a relativegroup, an acquaintance group, a family member group, etc. When the useradds the person within the social group, the user account of the userindicates the addition of the person within the social group.

In general, the systems and methods facilitate determination of anactivity level of an activity performed by a user at a location. Forexample, the systems and methods can determine that the user issedentary for a particular period of time when the user is at work. Asanother example, the systems and methods can determine that the user isactive when the user is at home. The activity or lack of activity istherefore contextually associated to a particular location. The locationcan be an address, map, or a combination of maps, addresses, activities,and/or predefined location identifiers or activities that occur atparticular locations (e.g., golf occurs at a golf course, swimmingoccurs at a swimming pool, etc.). By providing the user location contextto activities, the user is able to better view his or her actualactivity performance and better health decisions can be made regardingand/or adjustments can be made in lifestyle.

In some embodiments, a goal is generated. The goal is to be achievedwithin an amount of time. A current performance metric of a user iscalculated to determine whether the user will achieve the goal. When theuser achieves the goal, an award may be provided to the user. On theother hand, upon determining based on the current performance metricthat the user will not achieve the goal, a recommendation is made to theuser to change his/her activity and/or location. For example, it isrecommended that the user extend performing his/her activity for anadditional amount of time. As another example, it is recommended thatthe user go to a different location to perform the same activity theuser has been performing or a different activity than an activity theuser has been performing.

In various embodiments, a milestone to achieve the goal is generated. Itis measured whether the current performance metric is at the milestone.Upon determining that the current performance metric is at themilestone, the user may be provided with a reward. Otherwise, upondetermining that the user may not reach the milestone, the user isrecommended to perform the same activity that the user has beenperforming, or to perform a different activity than what is beingperformed by the user, or to visit a different location than a currentlocation of the user to perform the same activity that the user has beenperforming, or to visit a different location than a location of the userto perform a different activity than that the user has been performing.

In some instances, well known process operations have not been describedin detail in order not to unnecessarily obscure various embodimentsdescribed in the present disclosure.

FIG. 1A illustrates a variety of situations/activities in which a systemand/or method uses location data to segment a period of time intoidentifiable events, each event defining an activity for a period oftime. In one embodiment, location data is obtained for a time when theactivity is tracked, such as location data and/or characteristics of theactivity used to identify an event. As noted in detail below, a periodof time having associated tracking data can be segmented into one ormore events.

In the example of FIG. 1A, a user 112A wears a monitoring device 114A onhis arm while playing a sport, e.g., tennis Other examples of a sportinclude badminton, golf, running, bicycling, vehicle racing,racquetball, squash, soccer, etc. It should be understood that theexample of sports is provided, as such sports have particularidentifiable activity patterns. However, any activity, whether sportsrelated or not, can be tracked and associated to an event. For instance,another user 112B wears a monitoring device 114B on her arm whilewalking. Yet another user 112C wears a monitoring device 114C on his/herarm while doing yoga. Another user 112D wears a monitoring device 114Don his/her arm during sleep. Another user 112E wears a monitoring device114E on his/her arm while playing golf. Yet another user 112F wears amonitoring device 114F on his/her clothing part while riding a bicycle.Another user 112G wears a monitoring device 114G on his/her foot whilewalking a user 112H, e.g., a dog. In some embodiments, the user 112Gwalks other animals, e.g., a tiger, a cat, etc. The user 112H also wearsa monitoring device 114H on its arm. Another user 112I wears amonitoring device 114I on his arm during running.

In some embodiments, a user performs one or more of other activities,e.g., swimming, resistance training, rock climbing, skiing,snowboarding, hiking, skating, rollerblading, etc. It is noted that theactivities described herein are not limiting and that other activitiesmay be used.

It should be noted that in some embodiments, a user can wear, hold,append, strap-on, move, transport or carry a monitoring device whileperforming any type of activity, e.g., playing ping-pong, climbingstairs, descending stairs, hiking, sitting, resting, working, etc.Additionally, one user can be associated with more than one monitoringdevice, and such data can be processed and associated to the user'sactivity. In some embodiments, the data is selected from various devicesof the user based on a priority algorithm. In some embodiments, datafrom more than one device can be blended or alternated together todefine a more complete map of the activities.

Each monitoring device 114A, 114B, 114C, 114D, 114E, 114F, 114G, 114H,and 114I communicates with a network 176. In some embodiments, eachmonitoring device 114A, 114B, 114C, 114D, 114E, 114F, 114G, 114H, and114I communicates with the network 176 via a computing device, e.g., adesktop computer, a laptop computer, a smart phone, a tablet, a smartwatch, a smart television, etc.

Examples of the network 176 include the Internet and an Intranet. Thenetwork 176 may be a wide area network, a local area network, or acombination thereof. The network 176 may be coupled to one or moreservers, one or more virtual machines, or a combination thereof.

A server, a virtual machine, a controller of a monitoring device, or acontroller of a computing device is sometimes referred to herein as acomputing resource. Examples of a controller include a processor and amemory device.

As used herein, a processor includes an application specific integratedcircuit (ASIC), a programmable logic device (PLD), a processor, acentral processing unit (CPU), or a combination thereof, etc. Examplesof a memory device include a random access memory (RAM) and a read-onlymemory (ROM). A memory device may be a Flash memory, a redundant arrayof disks (RAID), a hard disk, or a combination thereof.

A computing resource performs data capture, which is reception ofactivity data from a monitoring device. Examples of activity datainclude, without limitation, calories burned by a user, blood pressureof the user, heart rate of the user, weight gained by a user, weightlost by a user, stairs ascended, e.g., climbed, etc., by a user, stairsdescended by a user, steps taken by a user during walking or running,floors descended by a user, floors climbed by a user, a number ofrotations of a bicycle pedal rotated by a user, sedentary activity data,a distance covered by a user during walking, running, or driving avehicle, a number of golf swings taken by a user, a number of forehandsof a sport played by a user, a number of backhands of a sport played bya user, or a combination thereof. In some embodiments, sedentaryactivity data is referred to herein as inactive activity data or aspassive activity data. In some embodiments, when a user is not sedentaryand is not sleeping, the user is active.

The data capture also includes capturing a geo-location of a monitoringdevice. For example, geographical location data 120A of the monitoringdevice 114A is determined by the monitoring device 114A and obtained bya computing resource. A geo-location is determined by a device locator,which is further described below. Examples of a geo-location includelatitude, radius, longitude, altitude, landmark, city, country, state,county, village, eatery, commercial place, commercial building,province, public place, or a combination thereof. In some embodiments,the geo-location data is obtained not by the monitoring device, but by acompanion device (e.g., such as a smart phone or other portable devicewith global positioning system (GPS) data collection capabilities).

In various embodiments, a device locator obtains a speed of a monitoringdevice or of a computing device. For example, a device locator of acomputing device determines a speed of the computing device and a devicelocator of a monitoring device determines a speed of the monitoringdevice. In various embodiments, a device locator of a device, e.g., amonitoring device, a computing device, etc., obtains an orientation ofthe device. In various embodiments, an orientation of a device includesa degree of rotation of the device with respect to an x axis, a y axis,and a z axis.

Similarly, geographical location data 120B of the monitoring device 114Bis determined by the monitoring device 114B and obtained by a computingresource, geographical location data 120C of the monitoring device 114Cis determined by the monitoring device 114C and obtained by a computingresource, geographical location data 120D of the monitoring device 114Dis determined by the monitoring device 114D and obtained by a computingresource, geographical location data 120E of the monitoring device 114Eis determined by the monitoring device 114E and obtained by a computingresource, geographical location data 120F of the monitoring device 114Fis determined by the monitoring device 114F and obtained by a computingresource, geographical location data 120G of the monitoring device 114Gis determined by the monitoring device 114G and obtained by a computingresource, geographical location data 120H of the monitoring device 114His determined by the monitoring device 114H and obtained by a computingresource, and geographical location data 120I of the monitoring device114I is determined by the monitoring device 114I and obtained by acomputing resource.

A geo-location of a monitoring device is used in conjunction withactivity data by a computing resource to perform data analysis. The dataanalysis is performed by a processor. For example, a level, e.g., anamount, etc., of an activity performed by a user at a geo-location isdetermined. Examples of activity level include a number of caloriesburned by a user, an amount of weight gained by a user, a heart rate ofa user, an amount of blood pressure of a user, an amount of weight lostby a user, a number of stairs ascended by a user, a number of stairsdescended by a user, a number of steps taken by a user during walking orrunning, a number of floors descended by a user, a number of floorsclimbed by a user, a number of rotations of a bicycle pedal rotated by auser, a distance covered by a vehicle operated by a user, a number ofgolf swings taken by a user, a number of forehands of a sport played bya user, a number of backhands of a sport played by a user, or acombination thereof, etc. The geo-location and the activity level arecombined and displayed to a user to monitor activity and/or health ofthe user over a period of time. As another example, a geo-location iscombined with an activity level to determine whether a user is still ata location, e.g., a house, a work place, an office, a gym, a sandwichshop, a coffee shop, etc. after performing the activity or has left thelocation after performing the activity. In this example, when it isdetermined that the user is at the location and the activity level hascrossed from a first side of a threshold to a second side of thethreshold, it is determined that the user has left the location.Moreover, in this example, when it is determined that the user is at thelocation and that the activity level has not crossed from the first sideto the second side, it is determined that the user is still at thelocation. In some embodiments, the first side of the threshold is belowthe threshold and the second side of the threshold is above thethreshold. In various embodiments, the first side of the threshold isabove the threshold and the second side is below the threshold.

In some embodiments, a user indicates to a monitoring device or acomputing device that the user has exited or entered a location. Forexample, the user logs into a user account and indicates via a userinterface of a monitoring device or an input device of a computingdevice that the user is exiting or entering a location. A processor,e.g., a processor of a server, a processor of a virtual machine, aprocessor of the computing device, or a processor of the monitoringdevice, or a combination thereof, etc., receives the indication from theuser. The processor determines a time at which the user indicates thatthe user is entering or exiting the location and indicates the time on agraphical user interface that includes event data. In variousembodiments, upon determining that the user has entered a location, theprocessor accesses the activity-location database to determine one ormore activities that may be performed by the user at the location andgenerates one or more activity identifiers of the activities.

In some embodiments, a computing resource performs data synchronization,which includes synchronization of activity data received from varioususers and synchronization of geo-locations of the users. For example,activity data from one user is displayed to another user when both theusers are within one location. As another example, activity data of oneuser is displayed to another user when both users are performing thesame activity, e.g., walking, running, etc. As yet another example,activity data of one user is displayed to another user when both usersare performing the same activity at the same location. As anotherexample, activity data is displayed to two or more users who performsimilar activities in disparate locations (e.g., a virtually sharedwalk).

In various embodiments, a computing resource recommends data to a userbased on activity data received from a monitoring device used by theuser and based on a location of the user. For example, when it isdetermined that a user is at a golf course and has not taken a number ofgolf swings, the recommendation data indicates to the user that the usermay take an additional amount of golf swings to achieve a goal. Asanother example, when it is determined that a user is not going to (oris unlikely to based on knowledge of the user's historical activitypatterns) reach his/her activity goal, e.g., walking a number of stepsover a time period, running a distance over a time period, climbing ordescending a number of stairs over a time period, bicycling for anamount of distance over a time period, bicycling for a number of pedalrotations of a bicycle over a time period, lifting a weight for a numberof times over a time period, hitting a forehand for a number of timesover a time period, hitting a backhand for a number of times over a timeperiod, etc., and it is determined that the user is at a location, thecomputing resource generates the recommendation data to indicate to theuser to perform an activity or to extend performing the activity at thelocation or at another location that is within a distance of thelocation. These recommendations can be provided as electronicnotifications to the user's device, the user's smart phone, to thetracking device, or some other user interface. The recommendations canalso be provided as voice notifications, in case the user is occupied ina task that limits viewing a screen, such as driving. The determinationthat the user is driving can be made using data regarding thespeed/motion of the device, location data (e.g., in a car), etc.

In some embodiments, a user may stand on a monitoring device thatdetermines a physiological parameter of the user. For example, a userstands on a scale that measures a weight, a body fat percentage, abiomass index, or a combination thereof, of the user.

FIG. 1B is a diagram of an embodiment of a method for determining anamount of movement 116A of the monitoring device 114G, e.g., a number ofstairs ascended by the monitoring device 114G, etc., over a period oftime t1. The amount of movement 116A occurs when the user 112A isperforming an activity of climbing stairs over the time period t1. Amethod of determining an amount of movement is performed by a positionsensor of a monitoring device. Additionally, the method cansimultaneously identify a location for the activity. The monitoringdevice 114G may be worn on the leg or foot (as depicted in FIG. 1B), orelsewhere on the body such as the wrist, forearm, upper arm, head,chest, or waist, or as an article of clothing such as a shirt, hat,pants, blouse, glasses, and the like.

A position sensor determines an amount of linear or angular movement ofan arm of a user or of another body part of a user. For example, aposition sensor determines that the user 112A wearing the monitoringdevice 114G on his leg has climbed a number of stairs, e.g., four,twenty, forty, etc., between positions A and B over the time period t1.

In some embodiments, instead of a number of stairs ascended, a positionsensor determines a number of stairs descended by the monitoring device114G.

FIG. 1C is a diagram of an embodiment of a method for determining anamount of movement 116B, e.g., an amount of distance traveled, a numberof steps traveled, etc., of the monitoring device 114E over a period oftime t2. For example, a position sensor determines that the user 112Awearing the monitoring device 114E on his hand has walked or ran anumber of steps, e.g., four, fifty, hundred, etc., between positions Cand D over the time period t2. The amount of movement 116B occurs whenthe user 112A is performing an activity of walking or running over thetime period t2.

FIG. 1D is a diagram of an embodiment of a method for determining anamount of movement 116C, e.g., an amount angular movement, etc., of themonitoring device 114E over a period of time t3. For example, a positionsensor determines that a hand of the user 112A wearing the monitoringdevice 114E on his/her hand is displaced by an angle over the timeperiod t3. The amount of movement 116C occurs when the user 112A isperforming a sports activity, e.g., golfing, playing tennis, playingping-pong, resistance training, etc., over the time period t3.

In some embodiments, a position sensor measures an angular displacementof a leg of the user 112A wearing the monitoring device 114G on his leg.

In various embodiments, a position sensor infers an activity performedby a user over a period of time based on one or more positions of amonitoring device that has the position sensor and that is worn by theuser. For example, upon determining that a difference between a first yposition and a second y position within a xyz co-ordinate system isgreater than an amount and that x positions between the two y positionsindicate a curved movement, a position sensor of a monitoring devicedetermines that the user 112A is playing golf. As another example, upondetermining that the user 112A covers less than a distance along anx-axis over a period of time, a position sensor of a monitoring deviceworn by the user 112A determines that the user 112A is walking and upondetermining that the user 112A covers more than the distance along thex-axis over the period of time, the position sensor determines that theuser 112A is running.

FIG. 1E is a diagram of an embodiment of a method for determining anamount of movement 116D, e.g., an amount angular movement, etc., of themonitoring device 114E over a period of time t4. For example, a positionsensor determines that the user 112A wearing the monitoring device 114Eon his/her hand is displaced by an angle over the time period t4. Theamount of movement 116D occurs when the user 112A is performing anactivity, e.g., a sports activity, an exercise activity, etc., over thetime period t4.

Examples of a period of time include a portion of a day, or a day, or aportion of a month, or a month, or a portion of a year, or a year, or aportion of a number of years, or a number of years.

FIG. 2A is a diagram of an embodiment of a system 250 for transferringdata, e.g., activity data, geo-location data, etc., between themonitoring device 114E and a server 228 via a computing device 164A andthe network 176. A wireless link 168 establishes a connection betweenthe monitoring device 114E and the computing device 164A. For example, aBluetooth device located within the monitoring device 114E establishes aBluetooth connection with a Bluetooth dongle interfacing with thecomputing device 164A via a Universal Serial Bus (USB) interface. Asanother example, an ad hoc Wi-Fi transmission and reception isestablished between a Wi-Fi adapter of the monitoring device 114E and aWi-Fi adapter of the computing device 164A. The wireless link 168 may bea Bluetooth or a Wi-Fi connection. A connection between the monitoringdevice 114E and the computing device 164A is used to transfer databetween the monitoring device 114E and the computing device 164A.

In some embodiments, a geo-location and/or a position determined by themonitoring device 114E is sent from the monitoring device 114E via thecomputing device 164A to a server or a virtual machine for processing,e.g., analysis, determining event data, etc. The server or the virtualmachine processes the geo-location and/or the position and sendsprocessed data, e.g., event data, maps, routes, etc., to the computingdevice 164A for display on the computing device 164A.

In some embodiments, instead of the wireless link 168, a wiredconnection is used between the monitoring device 114E and the computingdevice 164A.

Moreover, a wired connection 252 is established between the computingdevice 164A and the server 228 via the network 176. A wired connectionincludes network components, e.g., one or more routers, one or moreswitches, one or more hubs, one or more repeaters, one or more servers,one or more cables, or a combination thereof, etc.

The server 228 includes a processor 190, a network interface controller(NIC) 254 and a memory device 256. The processor 190 is coupled with thememory device 256 and the NIC 254. An example of a NIC includes anetwork interface card. In some embodiments, a modem is used instead ofa NIC.

The memory device 256 includes a user account 174 of the user 112A. Theuser 112A accesses the user account 174 when authentication information,e.g., username, password, fingerprints, footprints, thumbprints, or acombination thereof, etc., is authenticated by the processor 190 oranother server of the network 176. The authentication information isprovided by the user 112A via an input device, e.g., a mouse, a stylus,a keyboard, a keypad, a button, a touch screen, or a combinationthereof, etc., of a monitoring device or of a computing device.

The user account 174 is accessed by the user 112A to review graphicaluser interface (GUI) data 186 on a display device of the computingdevice 164A or of the monitoring device 114E. The GUI data 186 includesgeo-location data, a map, location in the form of location/activityidentifiers, activity data in the form of activity levels, and/orphysiological parameter of the user 112A. The activity data representsactivities performed by the monitoring device 114E. The processor 190associates, e.g., links, establishes a relationship between, etc.,geo-location data, location, activity data, and/or physiologicalparameter of the user 112A with the user account 174 to allow access ofthe geo-location data, activity data, a map, location, and/orphysiological parameter upon access of the user account 174. Thisrelationship provides context to the activity, both in terms of what theactivity was and where the activity occurred. This context can be usedto define events that occur over a period of time, and the events can bepresented on a GUI of a device, to provide useful information to a userregarding his or her activity over that period of time. Not only is theuser provide with activity data, but the activity data is displayed in agraphical or data organized manner that identifies segmented activitydata and associates it to the proper or inferred context.

In some embodiments, instead of using the monitoring device 114E toestablish the wireless connection 168, any other monitoring device, e.g.the monitoring device 114A (FIG. 1A) or a monitoring scale is used.

It should be noted that in several embodiments, data is transferred froma monitoring device via a computing device and the network 176 to avirtual machine instead of the server 228.

In some embodiments, instead of the wired connection 252, a combinationof a wireless connection and a wired connection is established.

In various embodiments, the user account 174 is stored in a memorydevice of a computing device or on a memory device of a monitoringdevice. In these embodiments, processing of a geo-location and/orposition is not done on the server 228 or a virtual machine to generateprocessed data, e.g., event data, location identifier, activityidentifier, etc. but is done by a processor of the computing deviceand/or by a processor of a monitoring device to generate the processeddata.

FIG. 2B is a diagram of an embodiment of a system 260 for transferringdata, e.g., activity data, geo-location data, etc., between themonitoring device 114E and the server 228 via a mobile computing device164B and the network 176. A wireless link 170 establishes a connectionbetween the monitoring device 114E and the mobile computing device 164B.The wireless link 170 may be a Bluetooth connection, a Wi-Fi connection,a near field connection, a radio frequency connection, or an opticalconnection, etc. In some embodiments, instead of the wireless link 168,a wired connection is used between the monitoring device 114E and themobile computing device 164B. A connection is used to transfer databetween the monitoring device 114E and the mobile computing device 164B.

Moreover, the server 228 and the mobile computing device 164B arecoupled with each other via a wireless connection 262, e.g., a Wi-Ficonnection, etc., the network 176, and a connection 264. The connection264 between the server 228 and the network 176 may be a wired or awireless connection.

FIG. 3A is a diagram of an embodiment of a system 270 to illustratecomponents of a monitoring device 108A. The system 270 includes themonitoring device 108A, a computing device 166, the network 176, and theserver 228.

The monitoring device 108A is an example of any of the monitoringdevices 114A, 114B, 114C, 114D, 114E, 114F, 114G, 114H, and 114I (FIG.1A). The monitoring device 108A includes an environmental sensor 272, aposition sensor 220, a time measurement device 232, a user interface274, a device locator 222, a display device 276, a processor 234, awireless communication device 278, and a memory device 280, all of whichare coupled with each other.

Examples of the device locator 222 include a GPS transceiver, a mobiletransceiver, etc. As used herein, a device locator may be referred to asa device or circuit or logic that can generate geo-location data. Thegeo-location data provides the appropriate coordinate location of thedevice or tracker, such as a location on a map or location in a room orbuilding. In some embodiments, a GPS device provides the geo-locationdata. In other embodiments, the geo-location data can be obtained fromvarious devices (e.g., cell towers, Wi-Fi device signals, other radiosignals, etc., which can provide data points usable to locate ortriangulate a location.

Examples of the environmental sensor 272 include a barometric pressuresensor, a weather condition sensor, a light exposure sensor, a noiseexposure sensor, a radiation exposure sensor, and a magnetic fieldsensor. Examples of a weather condition include a temperature, humidity,a pollen count, air quality, rain conditions, snow conditions, windspeed, a combination thereof, etc. Examples of light exposure includeambient light exposure, ultraviolet (UV) light exposure, or acombination thereof, etc. Examples of air quality include particulatecounts for varying sized particles, or level of carbon dioxide in air,or level of carbon monoxide in air, or level of methane in air, or levelof other volatile organic compounds in air, or a combination thereof.

Examples of the position sensor 220 include an accelerometer, agyroscope, a rotary encoder, a calorie measurement sensor, a heatmeasurement sensor, a moisture measurement sensor, a displacementsensor, an ultrasonic sensor, a pedometer, an altimeter, a linearposition sensor, an angular position sensor, a multi-axis positionsensor, or a combination thereof, etc. In some embodiments, the positionsensor 220 measures a displacement, e.g., angular displacement, lineardisplacement, a combination thereof, etc., of the monitoring device 108Aover a period of time with reference to an xyz co-ordinate system todetermine an amount of activity performed by the user 112A during theperiod of time. In some embodiments, a position sensor includes abiological sensor, which is further described below. In variousembodiments, a position sensor includes a motion sensor.

Examples of the time measurement device 232 include a watch, anoscillator, a clock, an atomic clock, etc. Examples of the userinterface 274 include an input device for interacting with the user112A. For example, the user interface 274 receives a selection of theGUI data 186 (FIG. 2A) from the user 112A. It should be noted that whenthe user interface 274 includes a touch screen, the touch screen 274 isintegrated within the display device 276.

Examples of a display device includes a liquid crystal display (LCD)device, a light emitting diode (LED) display device, a plasma displaydevice, etc. As an example, the display device 276 displays the GUI data186. In some embodiments, all GUIs described herein are displayed byrendering the GUI data 186.

Examples of the memory device 280 are provided above. Examples of thewireless communication device 278 include a Wi-Fi adapter, a Bluetoothdevice, etc.

In some embodiments, the processor 234 receives one or moregeo-locations measured by the device locator 222 over a period of timeand determines a location of the monitoring device 108A based on thegeo-locations and/or based on one or more selections made by the user112A via the user interface 274 and/or based on information availablewithin a geo-location-location database of the network 176. For example,the processor 234 determines that a location within thegeo-location-location database corresponds to one or more geo-locationsstored within the geo-location-location database. In this example, uponreceiving the geo-locations from the device locator 222, the processor234 determines the location based on the correspondence between thegeo-locations and the location in the geo-location-location database. Insome embodiments, the geo-location-location database includes a map of ageographical region, e.g., a city, a state, a county, a country, acontinent, a geographical area, world, etc. The map is generated by theserver 228 or another server based on one or more geo-locations.

The environmental sensor 272 senses and determines an environmentalparameter, e.g., a barometric pressure, a weather condition, an amountof light exposure, an amount of noise, an amount of radiation, an amountof magnetic field, or a combination thereof, etc., of an environment inwhich the monitoring device 108A is placed. The device locator 222determines a geo-location of the monitoring device 108A.

The time measurement device 232 determines an amount of time associatedwith one or more positions sensed by the position sensor 220, associatedwith one or more environmental parameters determined by theenvironmental sensor 272, associated with one or more geo-locationsdetermined by the device locator 222, and/or associated with one or morelocations determined by the processor 234. For example, the timemeasurement device 232 determines an amount of time for a number ofpositions that is reached by movement of the monitoring device 108A andthat is determined by the position sensor 220. As another example, thetime measurement device 232 determines an amount of time for a number ofgeo-locations reached by movement of the monitoring device 108A and thatis determined by the device locator 222.

The wireless communication device 278 establishes a wireless link withthe computing device 166 to send data, e.g., activity data, geo-locationdata, location data, a combination thereof, etc., to and/or receive thedata and/or instructions from the computing device 166. Each computingdevice 164A and 164B (FIGS. 2A & 2B) is an example of the computingdevice 166. The instructions from the computing device 166 may be tosend data, e.g., activity data, geo-location data, location data, acombination thereof, etc., to the computing device 166.

In some embodiments, the monitoring device 108A excludes the wirelesscommunication device 278. In these embodiments, the monitoring device108A communicates using a wired connection with the computing device166.

In various embodiments, the time measurement device 232 is integrated asa part of the position sensor 220 and/or as a part of the environmentalsensor 272 and/or as a part of the device locator 222.

In several embodiments, the monitoring device 108A excludes theenvironmental sensor 272.

In a number of embodiments, the monitoring device 108A includes abiological sensor coupled to the environmental sensor 272, the positionsensor 220, the time measurement device 232, the user interface 274, thedevice locator 222, the display device 276, the processor 234, thewireless communication device 278, and the memory device 280. Thebiological sensor is further described below.

FIG. 3B is a diagram of an embodiment of a system 290 to illustratecomponents of a monitoring device 108B. The system 290 includes themonitoring device 108B, the computing device 166, the network 176, andthe server 228. An example of the monitoring device 108B includes ascale. The monitoring device 108B is placed on a floor and the user 112Astands on the monitoring device 108B. The monitoring device 108Bincludes an environmental sensor 292, a biological sensor 294, a timemeasurement device 295, a user interface 296, a device locator 306, adisplay device 304, a processor 302, a wireless communication device300, and a memory device 298.

The environmental sensor 292 performs the same functions as that of theenvironmental sensor 272 (FIG. 3A) except that the environmental sensor292 is of a different, e.g., larger, smaller, etc., size compared to asize of the environmental sensor 272. In some embodiments, theenvironmental sensor 272 is used in the monitoring device 108B insteadof the environmental sensor 292.

The biological sensor 294 senses and determines a physiologicalparameter of the user 112A. For example, the biological sensor 294determines a weight of the user 112A. As another example, the biologicalsensor 294 determines a body mass index of the user 112A. As yet anotherexample, the biological sensor 294 determines a fingerprint or afootprint of the user 112A. As another example, the biological sensor294 determines a heart rate, a hydration level, a body fat, a bonedensity, and/or a bioimpedance of the user 112A. Examples of thebiological sensor 294 include a biometric sensor, a physiologicalparameter sensor, or a combination thereof.

The time measurement device 295 performs the same functions as that ofthe time measurement device 232 (FIG. 3A) except that the timemeasurement device 295 is different, e.g., larger, smaller, etc., insize compared to the time measurement device 232. As an example, thetime measurement device 295 determines an amount of time for a number ofphysiological parameters measured by the biological sensor 294.

In some embodiments, the time measurement device 232 is used in themonitoring device 108B instead of the time measurement device 295.

Similarly, the user interface 296 performs the same functions as that ofthe user interface 274 (FIG. 3A) and is of a different size than that ofthe user interface 274. In various embodiments, the user interface 274is used in the monitoring device 108B instead of the user interface 296.

Moreover, the memory device 298 performs the same functions as that ofthe memory device 280 (FIG. 3A) and is of a different size than that ofthe memory device 280. For example, the memory device 298 includes adifferent, e.g., larger, smaller, etc., number of memory cells comparedto memory cells of the memory device 280. In various embodiments, thememory device 280 is used in the monitoring device 108B instead of thememory device 298.

Also, the wireless communication device 300 performs the same functionsas that of the wireless communication device 278 (FIG. 3A) and is of adifferent size than that of the wireless communication device 278. Forexample, the wireless communication device 300 includes electricalcomponents that allow a transfer data at a different, e.g., higher,lower, etc., rate with the computing device 166 compared to a rate oftransfer of data between the wireless communication device 278 and thecomputing device 166. In various embodiments, the wireless communicationdevice 278 is used in the monitoring device 108B instead of the wirelesscommunication device 300.

Furthermore, the processor 302 performs the same functions as that ofthe processor 234 (FIG. 3A) and is of a different, e.g., larger,smaller, etc., size than that of the processor 234. For example, theprocessor 302 is of a size to achieve a different, e.g., higher, lower,etc., speed than that of the processor 234. In various embodiments, theprocessor 234 is used in the monitoring device 108B instead of theprocessor 302.

Moreover, the display device 304 performs the same functions as that ofthe display device 276 (FIG. 3A) and is of a different, e.g., larger,smaller, etc., size than that of the display device 276. In variousembodiments, the display device 276 is used in the monitoring device108B instead of the display device 304.

Also, the device locator 306 performs the same functions as that of thedevice locator 222 (FIG. 3A) and is of a different, e.g., larger,smaller, etc., size than that of the device locator 222. In variousembodiments, the device locator 222 is used in the monitoring device108B instead of the device locator 306.

In some embodiments, the monitoring device 108B includes a positionsensor (not shown) that performs the same functions as that of theposition sensor 220 (FIG. 3A). The position sensor of the monitoringdevice 108B is coupled to the environmental sensor 292, the biologicalsensor 294, the time measurement device 295, the user interface 296, thedevice locator 306, the display device 304, the processor 302, thewireless communication device 300, and the memory device 298. In variousembodiments, the position sensor 220 is implemented within themonitoring device 108B.

FIG. 4A is an isometric view of an embodiment of a monitoring device110A that is worn around a hand of a user or around a leg of the user.For example, the monitoring device 110A has a band that is unclasped toallow the monitoring device 110A to extend around a wrist of a user or aleg of the user. After the monitoring device 110A extends around thewrist, the band is clasped to fit the monitoring device 110A to thewrist of the user or to the leg of the user. As another example, themonitoring device 110A has an elastic band that is stretched to allow agrip of the monitoring device 110A to expand. The monitoring device 110Ais then slipped around a palm of a user to a wrist of the user or isslipped around a foot of the user to an ankle of the user. The elasticband is then released to fit the monitoring device 110A to the wrist ofthe user or the ankle of the user. In some embodiments, the monitoringdevice 110A is worn on a forearm or an upper arm of a user. In otherembodiments, the monitoring device can be carried, held, stored in abag, attached to a shoe, attached to a shirt or pants, etc. In otherembodiments, a single person can hold or wear multiple devices. Themultiple devices can track the same body part or object or cantrack/monitor multiple body parts, or objects. For instance, the usercan wear one on his/her wrist, one in a shoe, one on his pants, a hat, avisor, or any other object that can track some movement and/or locationof the user.

The monitoring device 110A includes a display screen 320 of a displaydevice that displays activity data of one or more activities performedby a user over a period of time, chronological data, geo-location data,or a combination thereof. Examples of a display screen include an LCDscreen, an LED screen, a plasma screen, etc. Examples of chronologicaldata include a time of day, a day, a month, a year, etc. The monitoringdevice 110A is an example of any of the monitoring devices 114A, 114B,114C, 114D, 114E, 114G, 114H, 114I (FIG. 1A), and 108A (FIG. 3A).

The monitoring device 110A includes one or more input devices thatallows a user to switch between displaying different types of data,e.g., from activity data to chronological data, from chronological datato activity data, from one type of activity data to another type ofactivity data, from geo-location data to activity data, from activitydata to geo-location data, etc., and to adjust or set chronologicaldata. Types of activity data include calories burned by a user, weightgained by a user, weight lost by a user, stairs ascended by a user,stairs descended by a user, steps taken by a user during walking orrunning, floors descended by a user, floors climbed by a user, rotationsof a bicycle pedal rotated by a user, distance covered by a vehicleoperated by a user, golf swings taken by a user, forehands of a sportplayed by a user, backhands of a sport played by a user, or acombination thereof, etc.

Again, it should be noted that in some embodiments, the monitoringdevice 110A is implemented as a watch, a wristband, or a bracelet, thatis worn/held by the user 112A.

FIG. 4B is an isometric view of an embodiment of a monitoring device110B that fits to an article of clothing or a belt worn by a user. Forexample, the monitoring device 110B has a pivoting clip that opens toallow the monitoring device 110B to extend with respect to a pocket of ashirt worn by a user. After the monitoring device 110B extends withrespect to the pocket, the clip is retracted to fit the monitoringdevice 110B to the pocket. The clip may be located between an upperportion 322 and a lower portion 324 of the monitoring device 110B toallow the upper portion 322 to extend from and pivot with respect to thelower portion 324.

The monitoring device 110B includes a display screen 326 that displaysactivity data, chronological data, geo-location data, or a combinationthereof. The monitoring device 110B is an example of the monitoringdevice 108A (FIG. 3A). The monitoring device 110B includes one or moreinput devices that allow a user to switch between displaying differenttypes of data and to adjust or set chronological data.

FIG. 4C is a view of an embodiment of a monitoring device 110C that fitsto an article of clothing or a belt worn by a user. For example, themonitoring device 110C has a flexible pivoting clip that opens to allowthe monitoring device 110C to extend with respect to a pocket of a pantworn by a user. After the monitoring device 110C extends around thepocket, the clip is retracted to fit the monitoring device 110C to thepocket. The clip may be located between an upper portion 328 and a lowerportion 330 of the monitoring device 110C to allow the upper portion 328to extend from and pivot with respect to the lower portion 330.

The monitoring device 110C includes a display screen 332 that displaysdata, e.g., activity data, chronological data, geo-location data, or acombination thereof, etc. The monitoring device 110C is an example ofthe monitoring device 108A (FIG. 3A). The monitoring device 110Cincludes one or more input devices that allow a user to switch betweendisplaying different types of data and to adjust or set chronologicaldata.

FIG. 4D is an isometric view of an embodiment of a monitoring device110D that fits with respect to an arm of a user. For example, themonitoring device 110D includes a hook and loop clasp that is extendedto loop around a wrist of a user and is then retracted to hook to thewrist. In some embodiments, the monitoring device 110D is implementedwithin a wrist watch. The monitoring device 110D includes a number ofbuttons 334A, 334B, and 334C to allow the monitoring device 110D toswitch between different types of data, e.g., geo-location data,location, chronological data, activity data, physiological parameter,etc., and to adjust or set chronological data.

The monitoring device 110D includes a display screen 336 that displaysactivity data, chronological data, geo-location data, physiologicalparameter, location data, the GUI data 186 (FIG. 2A), or a combinationthereof. The monitoring device 110D is an example of any of themonitoring devices 114A, 114 b, 114C, 114D, 114E, 114G, 114H, 114I (FIG.1A), and 108A (FIG. 3A).

It should be noted that in some embodiments, instead of beingimplemented as a watch, the monitoring device 110D is implemented as awristband or a bracelet that is worn by the user 112A.

Monitoring devices have shapes and sizes adapted for coupling to, e.g.,secured to, worn, etc., the body or clothing of a user. The monitoringdevices collect one or more types of physiological and/or environmentaldata from embedded sensors and/or external devices and communicate orrelay the data to other devices, including devices capable of serving asan Internet-accessible data sources, thus permitting the collected datato be viewed, for example, using a web browser or network-basedapplication. For example, while the user 112A is wearing or holding amonitoring device, the monitoring device may calculate and store theuser's step count using one or more sensors. The monitoring device thentransmits data representative of the user's step count to an account ona virtual machine, a computer, or a mobile phone, where the data may bestored, processed, and visualized by the user 112A.

Indeed, the monitoring device may measure or calculate a plurality ofactivity data and/or physiological parameters in addition to, or inplace of, the user's step count. These activity data and/orphysiological parameters include, but are not limited to, energyexpenditure, e.g., calorie burn, etc., floors climbed, floors descended,heart rate, heart rate variability, heart rate recovery, geo-location,elevation, speed and/or distance traveled, swimming lap count, swimmingstroke type and count detected, bicycle distance and/or speed, bloodpressure, blood glucose, skin conduction, skin temperature, bodytemperature, electromyography, electroencephalography, weight, body fat,caloric intake, nutritional intake from food, medication intake, sleepperiods, sleep phases, sleep quality, pH levels, hydration levels,respiration rate, or a combination thereof. The monitoring device mayalso measure or calculate parameters related to an environment aroundthe user 112A, such as, e.g., barometric pressure, weather conditions(e.g., temperature, humidity, pollen count, air quality, rain/snowconditions, wind speed, etc.), light exposure (e.g., ambient light, UVlight exposure, time and/or duration spent in darkness, etc.), noiseexposure, radiation exposure, magnetic field, or a combination thereof.

In some embodiments, the monitoring device quantifies work productivityagainst noise levels and/or against air quality and/or againsttemperature and/or against pressure and/or against humidity and/oragainst pollen count and the quantification is identified as a levelwithin event data. In several embodiments, the monitoring devicequantifies stress levels against noise levels and/or against an amountof time spent by the user 112A at work and/or against an amount of timespent by the user 112A exercising outside a work location and/or againstan amount of time spent by the user 112A in a gym and/or an amount oftime spent by the user 112A at his parent's home, and the quantificationis identified as a level within event data. In some embodiments, astress level is quantified, e.g., measured, determined, etc., based onheart rate variability (HRV) and/or galvanic skin response (GSR). TheHRV and/or the GSR are measured by a biological sensor.

Furthermore, a monitoring device or a computing device collating datastreams may calculate parameters derived from the activity data and/orphysiological parameters. For example, monitoring device or a computingdevice may calculate a user's stress and/or relaxation levels through acombination of heart rate variability, skin conduction, noise pollution,and sleep quality. In another example, a monitoring device or acomputing device may determine an efficacy of a medical intervention(e.g., medication) through a combination of medication intake, sleepand/or activity data. In yet another example, the monitoring device or acomputing device may determine an efficacy of an allergy medicationthrough the combination of pollen data, medication intake, sleep and/orother activity data.

FIG. 5 is a block diagram of an embodiment of the computing device 166.The computing device 166 includes a processor 226, a memory device 338,an input device 240, an input/output interface (I/O) 342, a devicelocator 344, a wireless communication device 346, an I/O 348, agraphical processing unit (GPU) 350, a display device 352, an I/O 354, aNIC 356, and an I/O 358, all of which are coupled to each other via abus 360.

An I/O is a parallel interface, a serial interface, or a USB interfacebetween two devices that are coupled to the I/O. For example, the I/O358 is an interface between the NIC 356 and the bus 360.

Examples of the processor 226 and the memory device 338 are providedabove. Moreover, examples of the input device 340 and the device locator344 are provided above. Furthermore, examples of the wirelesscommunication device 346, the display device 352, and the NIC 356 areprovided above. The GPU 350 executes a rendering technique to displaydata, e.g., GUI, web page, etc., on the display device 352.

The wireless communication device 346 receives geo-location data andactivity data from the wireless communication device 278 (FIG. 3A) ofthe monitoring device 108A and/or the wireless communication device 300(FIG. 3B) of the monitoring device 108B. The processor 226 determines agroup of activity data and a location/activity identifier based on theactivity data and the geo-location data.

In some embodiments, the computing device 166 includes a wiredcommunication device in addition to or instead of the wirelesscommunication device 300. Examples of the wired communication deviceinclude a USB interface, a parallel interface, and a serial interface.

In several embodiments, the user 112A provides via the user interface274 (FIG. 3A) of the monitoring device 108A to the processor 234 or viathe input device 340 (FIG. 5) of the computing device 166 to theprocessor 226 one or more locations, e.g., a home of the user 112A,coffee shop, work, gym, a home of a friend of the user 112A, a home of afamily member of the user 112A, a work place of the user 112A, a place,a street, a building, etc., that the user 112A visits over a period oftime. In some embodiments, the user 112A provides via the user interface274 (FIG. 3A) of the monitoring device 108A to the processor 234 or viathe input device 340 (FIG. 5) of the computing device 166 to theprocessor 226 a size of a location and a type of a location, e.g., workplace, sandwich place, pizza place, eatery, gym, golf course, park,running place, walking place, eating place, etc. Examples of a size of alocation include a number of floors within the location, a squarefootage of a location, a number of offices in the location, a number ofrooms in the location, a number of people that can fit in the location,a height of the location, a width of the location, a length of thelocation, a radius of a circle that identifies the location, a diameterof a circle that identifies the location, or a combination thereof.

The one or more locations, the type of location, and/or the size of thelocation received from the user 112A are sent by the monitoring device108A or by the monitoring device 108B via the computing device 166 andthe network 176 to the server 228 to be stored in thegeo-location-location database. In some embodiments, the one or morelocations, the type of location, and/or the size of the locationreceived from the user 112A are sent by the monitoring device 108A or bythe monitoring device 108B via the network 176 to the server 228 withoutusing the computing device 166 to be stored in the geo-location-locationdatabase.

In some embodiments, upon accessing the geo-location-location database,the processor 226 or the processor 234 determines that thegeo-location-location database does not include a location correspondingto one or more geo-locations visited by the user 112A over a period oftime. The processor 226 determines whether the user 112A is within aradius that includes one or more geo-locations of the user 112A. Upondetermining that the user 112A is within the radius for more than anumber of instances of time, the processor 226 generates a prompt toprovide to the user 112A via the display device 352 or the processor 234generates the prompt to provide to the user 112A via the display device276. The prompt requests the user 112A to provide the locationcorresponding to the one or more geo-locations that are within theradius and that are visited by the user 112A.

In a number of embodiments, the processor 234 determines that amongmultiple locations, a location within the geo-location-location databaseis closest to a geo-location of the user 112A wearing a monitoringdevice, and determines the location to correspond to thegeo-location-location of the user 112A.

In some embodiments, the processor 234 receives a selection, e.g., anexpansion of a bubble-shaped or another shaped graphical element ordisplayed on the display device 276, a contraction of a bubble-shaped oranother shaped graphical element displayed on the display device 276,etc., from the user 112A and the selection indicates that a locationcorresponds to a different set of geo-locations than that indicated bythe geo-location-location database. Upon receiving the selection, theprocessor 234 determines that the location corresponds to the differentset of geo-locations than that indicated by the geo-location-locationdatabase.

It should be noted that a graphical element has one or more graphicalproperties, e.g., a shape, a color, a shade, a texture, or a combinationthereof. For example, a graphical element includes a block, a line, abox, a dot, a pin, a circle, a bubble, or a combination thereof.

FIG. 6A is a flowchart of an embodiment of a method 102 for segmenting aperiod of time into identification of locations of a user performingactivities. The method 102 is executed by the monitoring device 108A(FIG. 3A).

The method 102 includes detecting, in an operation 104, an activity ofthe monitoring device 108A when the monitoring device 108A is worn bythe user 112A (FIG. 1A). It should be noted that when the monitoringdevice 108A is worn by the user 112A, the activity of the monitoringdevice 108A is the same as that of the user 112A. The activity includesan amount of movement of the monitoring device 108A and is performed fora period of time. In some embodiments, the activity includes a number ofcalories burned by the user 112A. Examples of the activity of the user112A detected by the monitoring device 108A include running, or walking,or jogging, or sleeping, or moving around, or a sports activity, orsleep, or a combination thereof.

The amount of movement of the user 112A includes an amount of movementof a body part of the user 112A. For example, the amount of movement ofthe user 112A includes an amount of stairs ascended by the user 112A, oran amount of stairs descended by the user 112A, a number of forehands ofa sport played by the user 112A, or a number of backhands of the sport,or a number of serves of the sport made by the user 112A, or a number oftimes a golf swing is made by the user 112A, or a number of times asoccer ball is kicked by the user 112A, or a number of times a ball isthrown by the user 112A, a number of rotations of a bicycle made by theuser 112A, or a number of times a paddle, e.g., a brake pedal, anaccelerator pedal, etc., of a vehicle is pushed by the user 112A, or anumber of times a hand movement is made by the user 112A, or a number oftimes a leg movement is made by the user 112A, or a number of times asteering wheel of a vehicle is rotated partially or fully by the user112A, or an amount of calories burned by the user 112A, or an amount ofdistance traveled by the user 112A, an amount of steps walked or ran bythe user 112A, or an amount of hours slept by the user 112A, or anamount of time for which the user 112A is active, or a combinationthereof.

The detection of the activity is performed by the position sensor 220(FIG. 3A) of the monitoring device 108A. For example, the positionsensor 220 determines the amount of movement of the user 112A. Theposition sensor 220 determines the amount of movement at each amount oftime, e.g., second, minute, hour, a fraction of a second, a fraction ofa minute, a fraction of an hour, etc., that is measured by the timemeasurement device 232 (FIG. 3A) of the monitoring device 108A.

The method 102 further includes obtaining, in an operation 118,geo-location data for the monitoring device 108A. For example, thegeo-location data includes a latitude, an altitude, and/or a longitudeof the monitoring device 108A. The geo-location data is obtained by thedevice locator 222 (FIG. 3A) of the monitoring device 108A. For example,signals are sent between the device locator 222 and another device,e.g., a cell tower, a satellite, etc., to determine a geo-location ofthe device locator 222, and the geo-location of the device locator 222is the same as a geo-location of the monitoring device 108A. Thegeo-location of the monitoring device 108A is the same as a geo-locationof the user 112A when the user 112A is wearing the monitoring device108A.

The method 102 also includes storing, in an operation 122, during theperiod of time of activity performed by the user 112A, the activity thatis detected in the operation 104 and the corresponding geo-location datathat is obtained in the operation 118. The geo-location data that isobtained in the operation 118 corresponds to the activity detected inthe operation 104 when the geo-location is obtained and the activity isdetected at the same time or during the same time period. For example,when the user 112A wearing the monitoring device 108A is performing anactivity at a longitude 1 and a latitude 1, a geo-location that includesthe longitude 1 and the latitude 1 corresponds to the activity. In thisexample, the position sensor 220 determines that the user 112A isperforming the activity and the device locator 222 determines that theuser 112 is at the longitude 1 and latitude 1 at the same time the user112A is performing the activity. To further illustrate, the detectedactivity corresponds to the geo-location data when the activity isdetected at a time the monitoring device 108A is located at thegeo-location.

The operation 122 of storing is performed by the memory device 280 (FIG.3A) of the monitoring device 108A or by a combination of the processor234 of the monitoring device 108A and the memory device 280 of themonitoring device 108A. For example, the processor 234 writes, e.g.,stores, etc., data to be stored in the memory device 280.

The method 102 further includes analyzing, in an operation 124, theactivity detected in the operation 104 and the correspondinggeo-location data obtained in the operation 118 to identify one or moreevents, e.g., an event 126 ₁, an event 126 ₂, an event 126 ₃, an event126 ₄, an event 126 ₅, an event 126 ₆, an event 126 ₇, an event 126 ₈,an event 126 ₉, an event 126 ₁₀, an event 128 ₁, an event 128 ₂, anevent 128 ₃, an event 128 ₄, an event 128 ₅, an event 128 ₆, etc., whichare described with reference to FIGS. 7A and 7E. The events 126 ₁, 126₂, 126 ₃, 126 ₄ 126 ₅, 126 ₆, 126 ₇, 126 ₈, 126 ₉, and 126 ₁₀ aredisplayed within an event region 730 of FIG. 7A. The events 128 ₁, 128₂, 128 ₃, 128 ₄, 128 ₅, and 128 ₆ are displayed within a GUI 394 (FIG.7E).

Each event occurs over a period of time. For example, the event 126 ₁occurs over a time period, e.g., from 12 AM to 8 AM, etc., and the event126 ₄ occurs over a time period, e.g., from a time between 8 AM and 9 AMto 3 PM, etc.

As further shown in FIG. 7A, each event 126 ₁, 126 ₂, 126 ₃, 126 ₄ 126₅, 126 ₆, 126 ₇, 126 ₈, 126 ₉, and 126 ₁₀ is a portion of a GUI 370,which is an example representation of the GUI data 186 (FIG. 2A). Forexample, each event 126 ₁, 126 ₂, 126 ₃, 126 ₄ 126 ₅, 126 ₆, 126 ₇, 126₈, 126 ₉, and 126 ₁₀ includes a textual and/or a graphical data portionof the GUI 370. To further illustrate, the event 126 ₄ includes agraphical data portion that shows activity levels, e.g., amounts, etc.,of an activity performed by the user 112A. Moreover, in thisillustration, the event 126 ₄ includes a time period during which theactivity is performed and indicates the activity, e.g., golfing, etc. Inthis illustration, the activity indicates a location, e.g., a golfcourse. As another illustration, the event 126 ₆ includes a graphicaldata portion that shows activity levels of an activity performed by theuser 112A. Moreover, in this illustration, the event 126 ₆ includes atime period during which the activity is performed and includes alocation, e.g., a home of the user 112A, etc., at which the activity isperformed.

Each event is associated, e.g., linked, corresponded, related, etc.,with a group of activity data and each group of activity data isassociated, e.g., linked, corresponded, etc., related, with alocation/activity identifier. For example, referring to FIG. 7A, theevent 126 ₄ includes a group 130A of activity data and the event 126 ₆includes a group 130B of activity data. The group 130A includes activitylevels of an activity performed by the user 112A during a period of timeand the group 130A is associated with a location/activity identifier132D. Similarly, the group 130B includes activity levels of an activityperformed by the user 112A during a period of time, e.g., a time periodbetween a time between 3 pm and 4 pm and a time between 5 pm and 6 pm,etc., and the group 130B is associated with a location/activityidentifier 132A.

Moreover, similarly, a group of activity data of the event 126 ₁ isassociated with the location/activity identifier 132A, a group ofactivity data of the event 126 ₂ is associated with a location/activityidentifier 132B, a group of activity data of the event 126 ₃ isassociated with a location/activity identifier 132C, a group of activitydata of the event 126 ₅ is associated with the location/activityidentifier 132C, a group of activity data of the event 126 ₇ isassociated with the location/activity identifier 132C, a group ofactivity data of the event 126 ₈ is associated with thelocation/activity identifier 132A, a group of activity data of the event126 ₉ is associated with a location/activity identifier 132C, and agroup of activity data of the event 126 ₁₀ is associated with alocation/activity identifier 132A. Furthermore, with reference to FIG.7E, a group of activity data of the event 128 ₁ is associated with alocation/activity identifier 134A and a group of activity data of theevent 128 ₃ is associated with a location/activity identifier 134B. Agroup of activity data is associated with a location/activity identifierto provide a context as to which activity is performed and where. Forexample, an amount of calories burned by a user are displayed in abackground in which an icon representing an activity of walkingperformed by the user is shown and/or an icon representing a public parkis shown. The amount of calories is burned when the user is walkingand/or in the public park and/or is walking in the public park.

Referring back to FIG. 6A, a location/activity identifier is generatedby the processor 234 using the geo-location data, which is obtained inthe operation 118, and/or activity data, which is obtained in theoperation 104. For example, the processor 234 (FIG. 3A) of themonitoring device 108A determines that the geo-location-locationdatabase indicates a correspondence between a location of the user 112Aand a set that includes one or more longitudes at which an activity isperformed by the user 112A, one or more latitudes at which the activityis performed, and/or one or more altitudes at which the activity isperformed, and assigns the location/activity identifier 132D torepresent the location. As another example, the processor 234 determinesthat a distance traveled by the user 112A in a period of time is withinan upper limit and a lower limit. The period of time is received fromthe time measurement device 232 of the monitoring device 108A. Thedistance traveled by the user 112A is received from the position sensor220 and/or the device locator 222 of the monitoring device 108A. Asanother example, the processor 234 receives a selection from the user112A via the user interface 274 (FIG. 3A) of the monitoring device 108Athat one or more geo-locations at which the user 112A performs anactivity correspond to a location of the user 112A, and assigns alocation/activity identifier to represent the location.

The operation 124 is performed by the processor 234 (FIG. 3A) based onthe activity detected in the operation 104 and/or the geo-location dataobtained in the operation 118, and a time period during which theactivity is performed. The processor 234 receives one or more amounts oftime of performance of an activity during a time period from the timemeasurement device 232 (FIG. 3A), and/or receives one or moregeo-locations at which the activity is performed during the time periodfrom the device locator 222 (FIG. 3A), and receives one or more activitylevels of the activity from the position sensor 220 (FIG. 3A) to performthe operation 124. For example, the processor 234 determines that theuser 112A is in a vehicle upon determining that a speed of travel of theuser 112A is greater than s₁ miles per hour. The speed s₁ is a runningor walking speed of one or more users. The processor 234 determines aspeed of travel of the user 112A based on geo-location data obtained inan hour of one or more geo-locations of the user 112. Geo-location datais received from the device locator 222 (FIG. 3A) of the monitoringdevice 108A and a measurement of the hour is received from the timemeasurement device 232 (FIG. 3A).

As another example, the processor 234 determines whether the user 112Ais in a vehicle, or is riding a bicycle or a skateboard, or isundergoing ambulatory motion based on a speed of the user 112A andmotion of a body portion of the user 112A. To illustrate, when theprocessor 234 determines that a speed of the user 112A is greater than apre-determined number of miles per hour and motion of the body portionis less than a pre-determined amount of motion, the processor 234determines that the user 112A is in a vehicle and is not walking orrunning. As another illustration, when the processor 234 determines thata speed of the user 112A is less than the pre-determined number of milesper hour and motion of the body portion is greater than thepre-determined amount of motion, the processor 234 determines that theuser 112A is performing the ambulatory motion. Examples of ambulatorymotion include walking, running, jogging, exercising, etc. An example ofthe body portion includes an arm of the user 112A. In variousembodiments, a speed of the user 112A is determined by a device locatoror a processor based on an amount of distance between two geo-locationsand time of the user 112A at each of the geo-locations. In someembodiments, a speed of the user 112A is determined by a position sensoror a processor based an amount of distance between two positions andtime of occurrence of each of the positions.

As yet another example, the processor 234 determines that the user 112Ais running upon determining that a speed of travel of the user 112A isgreater than s₂ miles per hour and a number of steps taken by the user112A is greater than ss₁ per hour. The speed s₂ is a walking speed ofone or more users. A number of steps are received by the processor 234from the position sensor 220 (FIG. 3A) of the monitoring device 108A. Asanother example, the processor 234 determines that the user 112A iswalking upon determining that a number of steps taken by the user 112Ais less than ss₁ per hour and greater than ss₂ per hour. As yet anotherexample, the processor 234 determines that the user 112A is in a vehicleupon determining that a speed of travel of the user 112A is greater thans₃ miles per hour and a number of steps taken by the user 112A is lessthan ss₃ per hour.

As another example, the processor 234 determines that the user 112A ismoving around upon determining that a number of steps taken by the user112A is less than ss₄ per hour. As yet another example, the processor234 determines that the user 112A is sedentary upon determining that theuser 112A is not walking, running, not moving around, and not in avehicle. As another example, the processor 234 determines that the user112A is sleeping upon determining that the user 112A is sedentary forgreater than an amount of time.

In some embodiments, the processor 234 determines a speed of travel ofthe user 112A based on geo-location data obtained over a period of timeof one or more geo-locations of the user 112 and the period of time.

The time period during which the activity is performed at a location isdetermined by the processor 234 based on a sum of amounts of timemeasured by the time measurement device 232 for performing the activityat one or more geo-locations corresponding to, e.g., included within,linked with, etc., the location.

The operation 124 of analyzing the detected activity and thecorresponding geo-location data during the period of time includesdetermining a time element of segregation of the activity detected atthe operation 104. For example, a period of time during which anactivity is performed is segmented into one or more time elements. Asanother example, a period of time during which an activity is performedis segmented into one or more time elements, and each time elementincludes a graphical property and/or text to represent the time element.Examples of a time element include a fraction of a minute, or a minute,or a fraction of an hour, or an hour, etc. Further examples of a timeelement are shown as a time element 144 ₁ and a time element 144 ₂ inFIG. 7A. The time element 144 ₁ is a time of day at which a golfactivity having an activity level is performed by the user 112A.Moreover, the time element 144 ₂ is another time of day at which a golfactivity having an activity level is performed by the user 112A. Theactivity level at the time element 144 ₂ is lower than the activitylevel at the time element 144 ₁. In some embodiments, the activity levelat the time element 144 ₂ is higher than or the same as the activitylevel at the time element 144 ₁. The time element 144 ₁ includes text,e.g., 9 AM, etc.

The operation 124 of analyzing the detected activity and thecorresponding geo-location data during the period of time furtherincludes determining an activity level for each time element. Forexample, an activity level 146 ₁ (FIG. 7A) is determined as beingperformed at the time element 144 ₁ and an activity level 146 ₂ (FIG.7A) is determined as being performed at the time element 144 ₂. Asanother example, the activity level 146 ₁ (FIG. 7A) is determined asbeing performed at the time element 144 ₁ and is determined to includetext and/or a graphical property, e.g., a dark gray bar, etc., and theactivity level 146 ₂ (FIG. 7A) is determined as being performed at thetime element 144 ₂ and is determined to include text and/or a graphicalproperty, a dark gray bar, etc.

The operation 124 of analyzing the detected activity and thecorresponding geo-location data during the period of time also includesdetermining a location/activity identifier of a location and/or activityfor each time element and for each activity level. For example, theprocessor 234 determines that an activity level that occurs at a timeelement is of an activity that occurs at one or more geo-locations thatcorrespond to a location and/or that correspond to an activity, e.g., ahome of the user 112, a building, a park, an office, golfing, walking,running, a commercial place, an eatery, a work place, a vehicle, a golfcourse, a sandwich shop, or any other location, etc., and determines alocation/activity identifier that represents the location and/oractivity.

As another example, the processor 234 determines that the activity level146 ₁ is of an activity that occurs at one or more geo-locations of agolf course and determines the location/activity identifier 132D thatrepresents golfing. In this example, the processor 234 accessescorrespondence between geo-location data and location data stored withinthe geo-location-location database to determine whether the one or moregeo-locations correspond to the golf course and/or also accessesposition data of the monitoring device 108A from the position sensor 220to determine that the activity is golfing. As yet another example, theprocessor 234 determines that the activity level 146 ₂ is of an activitythat occurs at one or more geo-locations of a golf course and determinesthe location/activity identifier 132D. In this example, the processor234 applies a selection received from the user 112A via the userinterface 274 (FIG. 3A) to determine that one or more geo-locations atwhich the activity level 146 ₂ occurs correspond to a golf course. Inthis example, the geo-locations at which the activity level 146 ₂ occursare the same or different from one or more geo-locations determined bythe processor 234 from the geo-location-location database to correspondto a golf course.

Examples of a location/activity identifier include a graphical element,e.g. an icon, an icon having a pointer, a symbol, a symbol having apointer, a trademark, a trademark having a pointer, a registered mark, aregistered mark having a pointer, an animation icon, an animation iconhaving a pointer, an animation, an animation having a pointer, a videoicon, a video icon having a pointer, a video, a video having a pointer,an audio icon, an audio icon having a pointer, an audio, an audio havinga pointer, a multimedia icon, a multimedia icon having a pointer, amultimedia, a multimedia having a pointer, or a combination thereof,etc., that represents a location at which the activity is performed.

A location/activity identifier has a graphical element and/or text. Forexample, the location/activity identifier 380B includes an icon of aperson walking. As another example, the location/activity identifier380D includes an icon of a person golfing with a golf club.

The operation 124 of analyzing the detected activity and thecorresponding geo-location data during the period of time furtherincludes associating the activity level with the time element and thelocation/activity identifier. Upon determining the location/activityidentifier for each time element and for each activity level, theprocessor 234 associates, e.g., establishes a link between, establishesa correspondence between, etc., the time element and the activity levelwith the location/activity identifier. For example, the processor 234establishes a link between the time element 144 ₁, the activity level146 ₁, and the location/activity identifier 132D. As another example,the processor 234 establishes a link between the time element 144 ₂, theactivity level 146 ₂, and the location/activity identifier 132D.

The operation 124 of analyzing the detected activity and thecorresponding geo-location data during the period of time also includesaggregating the associated activity levels and time elements over theperiod of time to indicate, using the associated location/activityidentifier, a location of occurrence of the activity levels and of agroup of activity data. The group of activity data includes the activitylevels and the period of time. The processor 234 aggregates, e.g.,combines, accumulates, etc., over a period of time the activity levelsand time elements that are associated with a location/activityidentifier of an activity. The period of time over which the processor234 aggregates is continuous, e.g., from 1 pm to 2 pm on a day, fromJanuary to February of a year, from year 2000 to year 2004 of a decade,etc.

The aggregated activity levels, time elements, and the associatedlocation/activity identifier are represented, by the processor 234,within one or more graphical elements and/or text of a background thatrepresent an event to generate or identify the event. For example, theprocessor 234 assigns one or more graphical elements to an area, withinthe GUI 370 (FIG. 7A), to generate the event 126 ₄ that includes thegroup 130A of activity data, the location/activity identifier 380D and abackground 150, e.g., a gray-shaded area, a shaded area, an area havinga graphical property, etc. The group 130A of activity data and thelocation/activity identifier 380D are overlaid on the background 150.The event 126 ₄ includes the time element 144 ₁ aligned, e.g.,vertically, horizontally, oblique, etc., with the activity level 146 ₁and further includes the location/activity identifier 132D including orattached to a pointer 380D. The pointer 380D points to the event 126 ₄that includes the activity level 146 ₁ and the time element 144 ₁.Similarly, as shown in FIG. 7A, a pointer 380A that is included withinor is attached to the location/activity identifier 132A points to theevent 126 ₁, a pointer 380B that is included within or is attached tothe location/activity identifier 132B points to the event 126 ₂, and apointer 380C that is included within or is attached to thelocation/activity identifier 132C points to the event 126 ₃.

It should be noted that in some embodiments, a location/activityidentifier does not include and is not attached to a pointer. Forexample, the event 126 ₄ includes the location/activity identifier 132Dwithout the pointer 380D.

In various embodiments, a group of activity data includes alocation/activity identifier in addition to one or more activity levelsand one or more time elements. For example, the group 130A of activitydata includes one or more activity levels, one or more time elements,and the location/activity identifier 380D.

In several embodiments, each activity level is assigned a graphicalproperty by the processor 234. For example, as shown in FIG. 7A, theactivity level 146 ₁ is assigned a graphical property 148 ₁ and theactivity level 146 ₂ is assigned a graphical property 148 ₂. Thegraphical property 148 ₂ may be the same or different from the graphicalproperty 148 ₁. For example, the graphical property 148 ₂ has the samecolor as that of the graphical property 148 ₁. As another example, thegraphical property 148 ₂ has the same texture and color as that of thegraphical property 148 ₁.

In some embodiments, the method 102 is performed by the monitoringdevice 108B (FIG. 3B) except instead of the operation 104, thebiological sensor 294 performs an operation of detecting a physiologicalparameter of the user 112A who is located on the monitoring device 108B.Moreover, in these embodiments, the operation 118 of obtaininggeo-location data for the monitoring device 108B is performed by thedevice locator 306 (FIG. 3B). Further, in these embodiments, theoperation 122 of storing the detected physiological parameter and thecorresponding geo-location data is performed by the processor 302 (FIG.3B) or by a combination of the processor 302 and the memory device 298(FIG. 3B). In these embodiments, the operation 124 of analyzing thedetected physiological parameter and the corresponding geo-location dataduring the period of time to identify one or more events is performed bythe processor 302 (FIG. 3B) of the monitoring device 108B.

FIG. 6B is a flowchart of an embodiment of a method 160 for segmenting aperiod of time into identification of locations of a user performingactivities. The method 160 is executed by the monitoring device 108A(FIG. 3A). In the method 160, the operations 104, 118, and 122 areperformed.

The method 160 includes transferring, e.g., sending, etc., in anoperation 162, from time to time, to the computing device 166 (FIG. 5)the activity that is detected at the operation 104 and that correspondsto the geo-location data that is obtained at the operation 118. Forexample, activity data is transferred periodically, e.g., every fractionof a second, every second, every minute, every fraction of a minute,etc., or aperiodically, e.g., randomly, etc., to the computing device166 upon reception of request from the computing device 166.

The operation 162 of transferring is performed by the wirelesscommunication device 278 (FIG. 3A) via a wireless link, e.g., thewireless link 168 (FIG. 2A), the wireless link 170 (FIG. 2B), etc.,between the monitoring device 108A (FIG. 3A) and the computing device166. For example, the wireless communication device 278 executes aBluetooth or a Wi-Fi protocol to transfer data to the computing device166 via a wireless link. In some embodiments in which a wired link isused between the monitoring device 108A and the computing device 166,the operation 162 of transferring is performed by a wired communicationdevice of the monitoring device 108A and the wired communication deviceis connected via a wired link to the wired communication device of thecomputing device 166. In various embodiments, the wireless communicationdevice 278 transfers data via a wireless communication link and thenetwork 176 (FIG. 3A) to the server 228 (FIG. 3A) without transferringdata via the computing device 166. In several embodiments, a wiredcommunication device of the monitoring device 108A transfers via a wiredcommunication link and the network 176 to the server 228 withouttransferring data via the computing device 166. For example, the wiredcommunication device of the monitoring device 108A executes acommunication protocol, e.g., a Transmission Control Protocol overInternet Protocol (TCP/IP), a User Datagram Protocol over InternetProtocol (UDP/IP), etc., to communicate data with the server 228 via thenetwork 176.

In some embodiments, the operations 104, 118, and 112 are performed bythe monitoring device 108B (FIG. 3B) with the changes described abovewith respect to the method 102 (FIG. 6A). Moreover, in theseembodiments, the operation 162 of transferring, from time to time, thedetected activity corresponding to the geo-location data to thecomputing device 166 is performed by the wireless communication device300 of the monitoring device 108B or by a wired communication device ofthe monitoring device 108B.

FIG. 6C is a diagram of an embodiment of a method 170 for segmenting aperiod of time into identification of locations of a user performingactivities. The method 170 is executed by the server 228 (FIGS. 2A &2B). The method 170 includes an operation 172 of enabling access to theuser account 174 (FIG. 2A) via the computing device 166 (FIG. 5) overthe network 176 (FIG. 2A). The processor 190 (FIG. 2A) of the server 228performs the operation 172 of enabling access to the user account 174.

The user 112A (FIG. 1A) uses the user interface 274 (FIG. 3A) of themonitoring device 108A or the input device 340 (FIG. 5) of the computingdevice 166 to provide the authentication information to access the useraccount 174. Upon receiving the authentication information via thenetwork 176, the processor 190 (FIG. 2A) of the server 228 or anotherprocessor of another server determines whether the authenticationinformation is authentic. Upon determining that the authenticationinformation is authentic or upon receiving the determination from theother processor of the other server, the processor 190 enables access tothe user account 174 to the user 112A. When access to the user account174 is enabled, a representation of the user account 174 is rendered bythe processor 234 on the display device 276 (FIG. 3A) of the monitoringdevice 108A or is rendered by the processor 226 of the computing device166 on the display device 352 (FIG. 5) of the computing device 166.

The method 170 further includes receiving, in an operation 178,monitoring data for the user account 174. The monitoring data includesthe activity detected at the operation 104 (FIGS. 6A & 6B) of themonitoring device 108A (FIG. 3A). The monitoring data includesgeo-location data obtained at the operation 118 (FIG. 6A).

The operation of receiving 178 is performed by the NIC 254 (FIG. 2A) ofthe server 228. The monitoring data is received, via the network 176(FIGS. 2A, 2B, & 3A), from the NIC 356 (FIG. 5) of the computing device166 that has received the monitoring data from the wirelesscommunication device 278 (FIG. 3A) of the monitoring device 108A or froma wired communication device of the monitoring device 108A. In someembodiments, the monitoring data is received from the wirelesscommunication device 278 of the monitoring device 108A and the network176 without use of the computing device 166.

In some embodiments, the NIC 254 applies a communication protocol toreceive the monitoring data. For example, the NIC 254 depacketizes oneor more packets to obtain the monitoring data.

The method 170 includes processing, in an operation 180, the monitoringdata to identify one or more events. The operation 180 of processing issimilar to the operation 124 (FIG. 6A) of analyzing the detectedactivity and the corresponding geo-location data during a period of timeto identify one or more events. For example, the operation 180 is thesame as the operation 124 except that the operation 180 is performed bythe processor 190 (FIG. 2A) of the server 228. The operation 180 isperformed to generate the GUI data 186 (FIG. 2A). The GUI data 186includes event data of one or more events. For example, the GUI data 186includes data that is rendered to display the GUI 370 (FIG. 7A). Asanother example, the GUI data 186 includes data that is rendered todisplay the GUI 394 (FIG. 7E).

The method 170 includes sending, in an operation 182, in response to arequest from a consuming device the GUI data 186 (FIG. 2A). Examples ofthe consuming device include the computing device 166 (FIG. 5) or themonitoring device 108A (FIG. 3A). For example, when the user 112A isprovided access to the user account 174 (FIG. 2A), a request is receivedfrom the NIC 356 (FIG. 5) to send the GUI data 186. Upon receiving therequest, the NIC 254 (FIG. 2A) of the server 228 applies a communicationprotocol for sending the GUI data 186 via the network 176 to the NIC 356of the computing device 166 for display on the display device 352 of thecomputing device 166. As another example, when the user 112A is providedaccess to the user account 174, a request is received from the wirelesscommunication device 278 of the monitoring device 108A or a wiredcommunication device of the monitoring device 108A via the network 176.Upon receiving the request, the NIC 254 (FIG. 2A) of the server 228applies a communication protocol for sending the GUI data 186 via thenetwork 176 to the wireless communication device 278 of the monitoringdevice 108A or to the wired communication device of the monitoringdevice 108A. The GUI data 186 is sent via the computing device 166 orwithout using the computing device 166.

The GUI data 186 includes graphics, e.g., graphical elements thatrepresent the events 146 ₁ and 146 ₂ (FIG. 7A), that represent thebackground 150 (FIG. 7A), that represent the location/activityidentifiers 132A, 132B, 132C, and 132D (FIG. 7A), etc. The GUI data 186further includes text, e.g., text 188A (“e.g., HOME” in FIG. 7A) thatdescribes, e.g., identifies, etc., a location that the user 112A hasreached during a day, text 188B (“e.g., HANS' PARENTS HOUSE” in FIG. 7A)that describes another location that the user 112A has reached duringthe day another time of the day, text 188C (e.g., “1 AM” in FIG. 7A)that represents a time of the day, text 188D (e.g., “2 AM” in FIG. 7A)that represents yet another time of the day, etc.

The graphics and text segments a period of time over which one or moreactivities are performed into events that are graphically distinct fromeach other. For example, as shown in FIG. 7A, the event 126 ₂ thatincludes activity data of an activity of walking is graphicallydistinct, e.g., has a lighter shade, etc., than the event 126 ₄ thatincludes activity data of an activity of golfing. As another example, asshown in FIG. 7A, an event includes activity data representing anactivity is represented by different graphical elements than an eventthat includes activity data representing the same or a differentactivity.

FIG. 6D is a flowchart of an embodiment of a method 200 for segmenting aperiod of time into identification of locations of a user performingactivities. The method 200 is executed by the monitoring device 108B(FIG. 3B).

The method 200 includes determining, in an operation 202, a geo-locationof the monitoring device 108B over a time period. The geo-location ofthe monitoring device 108B is determined by the device locator 306 (FIG.3B). The method 200 further includes determining, in an operation 204, aphysiological parameter of the user 112A over a period of time. Theoperation 204 is performed by the biological sensor 294 (FIG. 3B) of themonitoring device 108B. For example, the biological sensor 294 measuresa change in weight of the user 112A over a period of time for which thegeo-location is determined in the operation 202. As another example, thebiological sensor 294 measures a change in BMI of the user 112A over aperiod of time for which the geo-location is determined in the operation202. A period of time is measured by the time measurement device 395(FIG. 3B).

The method 200 also includes associating, in an operation 206, thegeo-location determined in the operation 202 with the physiologicalparameter determined in the operation 204 to facilitate determination ofa group of activity data and a location of the monitoring device 108B.The processor 302 (FIG. 3B) of the monitoring device 108B performs theoperation 206. For example, the processor 302 establishes a link betweenthe geo-location data and the physiological parameter. The processor 302determines a location of the monitoring device 108B based on thegeo-location data and the geo-location-location database. The processor302 further determines a group of activity data that includes one ormore amounts of a physiological parameter that provide a measure of anactivity performed over a period of time. For example, when the user112A exercises over a period of time, the user 112A may lose weight. Asanother example, when the user 112A is sedentary over a period of time,the user 112A may gain weight. The processor 302 then generates eventdata that includes a relation between the location and the group ofactivity data. For example, the processor 302 determines that one ormore amounts of a physiological parameter occur at a location over aperiod of time and generates a relationship, e.g., correspondence, link,etc., between the amounts, the location, and the time period.

FIG. 6E is a flowchart of an embodiment of a method 210 for segmenting aperiod of time into identification of locations of a user performingactivities. The method 210 is performed by one or more monitoringdevices, e.g., the monitoring device 108A, the monitoring device 108B, acombination thereof, etc.

The method 210 includes an operation 212 of detecting an activity and/ora physiological parameter of the user 112A with one or more monitoringdevices for a period of time. For example, the position sensor 220 ofthe monitoring device 108A (FIG. 3A) detects an activity performed bythe user 112A and the biological sensor 294 of the monitoring device108B (FIG. 3B) detects a physiological parameter of the user 112A.

The method 210 further includes an operation 214 of obtaininggeo-location data for the monitoring devices for the period of time forwhich the operation 212 is performed. For example, geo-location data ofgeo-location of the monitoring device 108A is measured by the devicelocator 222 of the monitoring device 108A (FIG. 3A) and geo-locationdata of geo-location of the monitoring device 108B is measured by thedevice locator 306 of the monitoring device 108B (FIG. 3B). A period oftime is measured by the time measurement device 232 (FIG. 3A) of themonitoring device 108A and by the time measurement device 295 of themonitoring device 108B (FIG. 3B).

The method 210 includes an operation 216 of saving, in an operation 216,the detected physiological parameter and the detected activity in theoperation 212. For example, the operation 216 of saving the detectedactivity is performed by the processor 234 of the monitoring device 108Aand/or by the processor 234 and the memory device 280 of the monitoringdevice 108A. As another example, the operation 216 of saving thedetected physiological parameter is performed by the processor 302 ofthe monitoring device 108B and/or by the memory device 298 (FIG. 3B) ofthe monitoring device 108B.

The method 210 includes an operation 218 of transferring, from time totime, the detected physiological parameter and the detected activitycorresponding to the geo-location data to the computing device 166 (FIG.5) and/or to the server 228. For example, the operation 218 oftransferring is performed by the wireless communication device 278 (FIG.3A) of the monitoring device 108A or by a wired communication device ofthe monitoring device 108A. As another example, the operation 218 oftransferring is performed by the wireless communication device 300 ofthe monitoring device 108B or by a wired communication device of themonitoring device 108B. The detected activity and the detectedphysiological parameter are transferred wirelessly to the wirelesscommunication device 224 (FIG. 5) of the computing device 166. In someembodiments, the detected activity and the detected physiologicalparameter are transferred via a wired link, e.g., a cable, a wire, etc.,to the wired communication device (not shown) of the computing device166. In several embodiments, the detected activity and the detectedphysiological parameter are transferred via a wired link or acombination of a wireless link and a wired link and the network 176 tothe server 228 without use of the computing device 166.

Moreover, in some embodiments, the geo-location data is alsotransferred, from time to time, to the computing device 166 and/or tothe server 228. For example, the wireless communication device 278 (FIG.3A) of the monitoring device 108A transfers geo-location data to thewireless communication device 224 of the computing device 166 or a wiredcommunication device of the monitoring device 108A transfers thegeo-location data to the wired communication device of the computingdevice 166. As another example, the geo-location data is transferredwirelessly by the wireless communication device 300 of the monitoringdevice 108B or by a wired communication device of the monitoring device108B to the computing device 166. In several embodiments, thegeo-location data is transferred via a wired link or a combination of awireless link and a wired link and the network 176 to the server 228without use of the computing device 166.

FIG. 6F is a flowchart of an embodiment of a method 221 for segmenting aperiod of time into identification of locations of a user performingactivities. The method 221 is performed by the monitoring device 108A,the monitoring device 108B, by the computing device 166, or acombination thereof.

The method 221 includes receiving, in an operation 223, detectedactivity and/or physiological parameter of the user 112A. For example,the processor 234 (FIG. 3A) of the monitoring device 108A receivesdetected activity from the position sensor 220 (FIG. 3A). As anotherexample, the processor 302 of the monitoring device 108B receivesdetected physiological parameter from the biological sensor 294 (FIG.3B) of the monitoring device 108B. As yet another example, the processor226 of the computing device 166 (FIG. 5) receives the detected activityfrom the monitoring device 108A and/or receives the physiologicalparameter from the monitoring device 108B.

The method 221 includes an operation 227 of classifying detectedactivity and/or the physiological parameter. For example, the processor234 (FIG. 3A) of the monitoring device 108A classifies the amount ofmovement into walking, running, sedentary, sleeping, moving around, orplaying a sport. As another example, the processor 302 of the monitoringdevice 108B classifies the physiological parameter into a type ofphysiological parameter, e.g., BMI, heart rate, blood pressure, weight,etc. As another example, the processor 226 of the computing device 166classifies the detected activity and/or the physiological parameter.

The method 221 further includes an operation 229 of determining alocation of the user 112A. For example, the processor 234 of themonitoring device 108A determines a location of the user 112A based ongeo-location data and/or based on detected activity and/or based on thegeo-location-location database. The geo-location data is received by theprocessor 234 from the device locator 222 of the monitoring device 108Aand the detected activity is received by the processor 234 from theposition sensor 220 (FIG. 3A) of the monitoring device 108A. Moreover, adetermination of a location based on the geo-location data is made bythe processor 234 based on the geo-location data and/or the activitydata and/or the geo-location-location database.

As another example, the processor 226 of the computing device 166determines a location of the user 112A based on geo-location data and/orbased on detected activity and/or based on a physiological parameter,and/or based on the geo-location-location database. The geo-locationdata is received by the processor 226 from the device locator 222 of themonitoring device 108A or from the device locator 306 of the monitoringdevice 108B and the detected activity is received by the processor 226from the position sensor 220 (FIG. 3A) of the monitoring device 108Aand/or a physiological parameter is received from the biological sensor294 of the monitoring device 108B. Moreover, a determination of alocation based on the geo-location data is made by the processor 234based on the geo-location data and/or the activity data and/or thephysiological parameter and/or the geo-location-location database. Forexample, upon determining that there is a lack of change beyond anamount in a physiological parameter over a period of time, the processor234 determines that the user 112A has not left one or more geo-locationsthat corresponds to his/her home during the period of time.

In some embodiments, the processor 226 classifies an activity based on aphysiological parameter of the user 112A, and/or a movement of the user112A, and/or a location of the user 112A. For example, a heart rate ofthe user 112A is monitored, a movement of an arm of the user 112A isdetermined, and a location of the user 112A is determined to determinethat the user 112A is training with weights in a gym and not swimming inthe gym. As another example, an amount of calories burned by the user112A is measured, a movement of an arm of the user 112A is determined,and a location of the user 112A is determined to indicate that the user112A is swimming in a gym as opposed to running in the gym.

The method 221 further includes an operation 231 of overlaying of theclassified activity performed by the user 112A and/or of the classifiedphysiological parameter of the user 112A and/or of a location arrived atby the user 112A on a map. For example, the processor 234, the processor302, or the processor 226 determines generates event data that includesthe map, the classified activity, and/or the classified physiologicalparameter. In some embodiments, instead of the operation 231, anoperation of overlaying the map is performed on the classified activityand/or the classified physiological parameter and/or the locationarrived at by the user 112A.

In various embodiments, event data is generated based on positions thatare obtained by a position sensor of a monitoring device andgeo-locations obtained by a device locator of the computing device 166.The geo-locations are of the computing device 166 when carried by theuser 112A. The computing device 166 transfers the geo-locations via aNIC and the network 176 to the server 228. Moreover, the monitoringdevice transfers the positions via a communication device and thenetwork 176 to the server 228. The server 228 receives the geo-locationsand the positions and generates the event data. In some embodiments,instead of the server 228, a virtual machine generates the event data.

In some embodiments, a monitoring device receives the geo-location datathat is obtained by a device locator of the computing device 166 andgenerates event data based on positions and the geo-locations. Themonitoring device includes a position sensor that determines thepositions of the monitoring device. The monitoring device receives thegeo-locations via a communication device of the monitoring device and acommunication device of the computing device 166. The geo-locations areof the computing device 166 when carried by the user 112A.

In several embodiments, the computing device 166 receives positions thatare obtained by a position sensor of a monitoring device and generatesevent data based on positions and the geo-locations. The geo-locationsare of the computing device 166 when carried by the user 112A. Themonitoring device includes a position sensor that determines thepositions of the monitoring device.

In various embodiments, a portion of the event data is generated by aprocessor of a monitoring device and the remaining portion is generatedby a processor of the computing device 166. In several embodiments, aportion of event data is generated by a processor of a monitoringdevice, another portion of the event data is generated by a processor ofthe computing device 166, and the remaining portion is generated by aprocessor of the server 228. In various embodiments, a portion of eventdata is generated by a processor of a monitoring device, another portionof the event data is generated by a processor of the computing device166, and the remaining portion is generated by a virtual machine. Insome embodiments, a portion of event data is generated by a processor ofa monitoring device and the remaining portion is generated by a virtualmachine or by the server 228. In various embodiments, a portion of eventdata is generated by a processor of the computing device 166 and theremaining portion is generated by a virtual machine or by the server228.

FIG. 7A is an embodiment of the GUI 370 that displays the events 126 ₁thru 126 ₁₀. In some embodiments, the processor 234 (FIG. 3A)highlights, e.g. bolds, colors, shades, etc., an activity level that ishigher than or lower than the remaining activity levels by a threshold.The highlight distinguishes the activity level from one or more activitylevels of one or more events that occur during a period of time. Forexample, the processor 234 provides a different color to an activitylevel 402 compared to remaining activity levels of the event 126 ₁₀ whenthe processor 234 determines that the activity level 402 is greater thanthe remaining activity levels by a threshold.

The GUI 370 is rendered by the processor 234 of the monitoring device108A to be displayed on the display device 276 (FIG. 3A) of themonitoring device 108A or by the processor 226 (FIG. 5) of the computingdevice 166 to be displayed on the display device 352 (FIG. 5) of thecomputing device 166.

The processor 234 or the processor 226 combines amounts of time of acommon activity over one or more periods of time to indicate a combinedamount of time, e.g., a combined amount of time 138 ₁, a combined amountof time 138 ₂, a combined amount of time 138 ₃, a combined amount oftime 138 ₄, etc., of performance of the common activity and a level,e.g., a level 140 ₁, a level 140 ₂, a level 140 ₃, a level 140 ₄, etc.,of the common activity performed. For example, as shown in FIG. 7A, theuser 112A drove a vehicle for 1 hour and 1 minute on a date 308 of March1, Thursday. As another example, the processor 234 or the processor 226sums periods of time for which the user 112A performed the commonactivity on the date 308. To illustrate, a period of time of occurrenceof the event 126 ₂, a period of time of occurrence of the event 126 ₅, aperiod of time of occurrence of the event 126 ₇, and a period of time ofoccurrence of the event 126 ₉ are summed to determine a total timeperiod of occurrence of a common activity of driving a vehicle.

Examples of a common activity are the same as that of an activity exceptthat the common activity is the same over multiple periods of time. Forexample, a common activity is walking, running, golfing, etc.

In various embodiments, the processor 234 or the processor 226 combinesactivity levels of performance of the common activity over the combinedamount of time to generate a combined activity level for each commonactivity. For example, activity levels of the event 126 ₂, activitylevels of the event 126 ₅, activity levels of the event 126 ₇, andactivity levels of the event 126 ₉ are summed to generate a combinedactivity level of a common activity of driving over the total timeperiod to generate a combined activity level 140 ₄. Similarly, othercombined activity levels 140 ₁, 140 ₂, and 140 ₃ are generated.

Moreover, in some embodiments, the processor 234 or the processor 226combines amounts of time of one or more activities performed at a commonlocation over one or more periods of time to generate a combined amountof time, e.g., a combined amount of time 138 ₅, a combined amount oftime 138 ₆, a combined amount of time 138 ₇, etc., of performance of theone or more activities at the common location. For example, time ofperformance of all activities performed at a home of the user 112 on thedate 308 are combined to generate the combined amount of time 138 ₅. Asanother example, time of performance of all activities performed at anoffice of the user 112 on March 1 are combined to generate the combinedamount of time 138 ₆. A common location is a location at which one ormore activities, e.g., a common activity, etc., are performed over oneor more periods of time.

In several embodiments, the processor 234 or the processor 226 combinesactivity levels of performance of the one or more activities at thecommon location over a combined amount of time to generate a combinedactivity level, e.g., a combined activity level 140 ₅, a combinedactivity level 140 ₆, a combined activity level 140 ₇, etc., of one ormore activities performed at the common location. For example, activitylevels of an activity of walking done by the user 112A at a home of theuser 112A on the date 308 are combined to generate the combined activitylevel 140 ₅. As another example, activity levels of one or moreactivities performed during the events 126 ₁, 126 ₆, and 126 ₁₀ arecombined to generate the combined activity level 140 ₅.

The GUI 370 further includes a reverse button 410 and a forward button412. The user 112A selects the reverse button 410 via the user interface274 (FIG. 3A) or via the input device 340 (FIG. 5) to view a GUI thatdisplays one or more events, one or more combined activity levels,and/or one or more combined amounts of time on a date prior to the date308. Similarly, The user 112A selects the forward button 412 via theuser interface 274 (FIG. 3A) or via the input device 340 (FIG. 5) toview a GUI that displays one or more events, one or more combinedactivity levels, and/or one or more combined amounts of time on a dateafter the date 308.

In various embodiments, the GUI 370 includes a time at which there is achange in an activity level beyond a limit in an amount of time. Forexample, the GUI 370 includes a wake-up time 414 and a bed time 416. Theposition sensor 220 (FIG. 3A) determines an amount of activity and basedon the amount, the processor 234 or the processor 226 determines whetherthe amount of activity has crossed the limit in an amount of time. Upondetermining that the amount of activity has crossed the limit in anamount of time, the processor 234 or the processor 226 indicates, e.g.,highlights, etc., a time at which the level is crossed on the GUI 370.For example, the processor 234 highlights the wake-up time 414 and thebed time 316.

It should be noted that a GUI generated by the processor 234 isdisplayed on the display device 276 (FIG. 3A), a GUI generated by theprocessor 302 is displayed on the display device 304 (FIG. 3B), and aGUI generated by the processor 226 is displayed on the display device352 (FIG. 5).

It should further be noted that in some embodiments, any GUI describedherein as being generated by the processor 234 or by the processor 226for display may instead be generated by the processor 302 of themonitoring device 108B for display on the display device 304.

In some embodiments, event data includes an environmental parameter thatis received from the environmental sensor 272 of the monitoring device108A by the processor 234 (FIG. 3A) or from the environmental sensor 292of the monitoring device 108B by the processor 302 (FIG. 3B) or from theenvironmental sensor 272 via the wireless communication device 278 (FIG.3A) of the monitoring device 108A by the NIC 356 (FIG. 5) of thecomputing device 166 or from the environmental sensor 292 via thewireless communication device 300 (FIG. 3A) of the monitoring device108B by the NIC 356 (FIG. 5) of the computing device 166.

In several embodiments, the processor 226 or the processor 234 does notgenerate event data when an activity of the event data occurs for lessthan a period of time, e.g., two minutes, three minutes, etc.

In a number of embodiments, the processor 226 or the processor 234replaces a current location identifier with a previous and a futurelocation identifier when the user 112A is at the previous, current, andfuture locations within a time limit and when the previous locationidentifier and the future location identifier are the same. The previouslocation is a location at which the user 112A was before arriving at thecurrent location. The current location is a location at which the user112A is before the user 112A arrives at the future location. Forexample, the processor 234 determines based on the correspondencebetween one or more geo-locations, one or more positions of the user112A, and the previous location and based on the correspondence betweenone or more geo-locations, one or more positions of the user 112A, andthe future location that the previous location and the future locationare the same.

In this example, the processor 234 further determines that the currentlocation is different from the previous and future locations and theuser 112A has arrived at the previous, current, and future locationswithin a time limit that is received from the time measurement device232. In this example, the processor 234 determines that the currentlocation is different from the previous locations based on thecorrespondence between one or more geo-locations, one or more positionsof the user 112A, and the previous location and based on thecorrespondence between one or more geo-locations, one or more positionsof the user 112A, and the future location and based on thecorrespondence between one or more geo-locations, one or more positionsof the user 112A, and the current location. In this example, theprocessor 234 determines that the current location is the same as theprevious and future locations upon determining that the previous andfuture locations are the same and that the user 112A arrives at theprevious, current, and future locations within the time limit.

In several embodiments, the processor 226 or the processor 234 replacesa current activity identifier with a previous and a future activityidentifier when the user 112A performs the previous, current, and futureactivities within a time limit and when the previous activity identifierand the future activity identifier are the same. The previous activityis an activity that the user 112A performs before performing the currentactivity and the current activity is an activity that the user 112Aperforms before performing the future activity. For example, theprocessor 234 determines based on positions of the user 112A and/orgeo-location data of the user 112A that the previous activity and thefuture activity are the same and that the current activity is differentfrom the previous and the future activities. In this example, theprocessor 234 further determines that the previous, current, and futureactivities are performed within a time limit that is received from thetime measurement device 232. In this example, the processor 234determines that the current activity is the same as the previous andfuture activities upon determining that the previous and futureactivities are the same and that the user 112A performs the previous,current, and future activities within the time limit.

In some embodiments, the processor 226 or the processor 234 applies aMarkov model to determine whether to replace the current locationidentifier that is different from the previous and future locationidentifiers with the previous or future location identifier. In a numberof embodiments, the processor 226 or the processor 234 applies a Markovmodel to determine whether to replace the current activity identifierthat is different from the previous and future activity identifiers withthe previous or future activity identifier.

In some embodiments, a user resizes and/or repositions an overlay, e.g.,an activity identifier, a location identifier, etc., to improve theprecision of an event. For example, an overlay indicates that the user112A is performing an activity at a first activity level at a time. Theuser 112A changes a position and/or size of the overlay to indicate thatthe user 112A is performing the activity at a second activity level atthe time. The first and second activity levels are displayed within thesame GUI. The user 112A changes a position and/or size of an overlay viaan input device of the computing device 166 or via a user interface of amonitoring device.

FIG. 7B is a diagram of a GUI 420 that is generated by executing themethod 102 (FIG. 6A), 160 (FIG. 6B), 170 (FIG. 6C), 210 (FIG. 6E), or221 (FIG. 6F). A map 422 includes a location, e.g., an aquarium, etc.,visited by the user 112A and further includes a route to the location.The map 422 is displayed within the GUI 420. The map 422 is generatedbased on geo-location data. Moreover, the GUI 420 includes a timeline423 of activities performed by the user 112A on a date 424 of Mar. 1,2012. The date 424 is displayed within the GUI 420 on top of the map422.

The user 112A selects the date 424 among multiple dates displayed on topof the map 422 via the user interface 274 (FIG. 3A) of the monitoringdevice 108A or via the input device 340 (FIG. 5) of the computing device166. When the date 424 is selected, the processor 234 of the monitoringdevice 108A (FIG. 3A) generates the GUI 420 to display the GUI 420 onthe display device 276 (FIG. 3A) or the processor 226 (FIG. 5) of thecomputing device 166 generates the GUI 420 to display the GUI 420 on thedisplay device 352 (FIG. 5) of the computing device 166.

The GUI 420 includes events 424 ₁, 424 ₂, 424 ₃, 424 ₄, 424 ₄, 424 ₅,424 ₆, and 424 ₇. The event 424 ₄ includes activity levels of anactivity performed at the aquarium by the user 112A.

FIG. 7C is a diagram illustrating a method for establishing boundariesbetween two locations over one or more periods of time. A boundary is aboundary of a location. A boundary also indicates a time at which theuser 112A enters or exits a location having the boundary. For example, aboundary A includes outside walls of a home of the user 112A and a timeat which the user 112A enters the home or exits the home. As anotherexample, a boundary B includes outside walls of a building where theuser 112A works and a time at which the user 112A enters the building orleaves the building. As yet another example, a boundary C includesoutside walls of a sandwich shop and a time at which the user 112Aenters the sandwich shop or leaves the sandwich shop. As anotherexample, a boundary D includes a line that limits an area of a golfcourse and a time at which the user 112A enters the golf course orleaves the golf course. As an example, a boundary E includes a body of avehicle and a time at which the user 112A enters the vehicle or leavesthe vehicle.

The processor 234 of the monitoring device 108A (FIG. 3A) or theprocessor 226 (FIG. 5) of the computing device 166 determines boundarieswhere the user 112A arrives at, e.g., enters, etc., and departs from,e.g., exits, etc., a location. For example, the processor 234 receivesfrom the device locator 222 (FIG. 3A) a geo-location 1 of the monitoringdevice 108A. Continuing with the example, the processor 234 determinesthat the geo-location 1 corresponds to a location 1, e.g., a street, avehicle, etc., outside a location 2, e.g., a building, a street, etc.The location 2 corresponds to a geo-location 2. The processor 234determines that the user 112A is at the location 1 at a time tx and atthe location 2 at a time ty. In this example, the processor 226 receivesthe geo-location 1 from the device locator 222 and the geo-location 2from the device locator 222 and the times tx and ty from the timemeasurement device 232 (FIG. 3A). In this example, there is a lack ofgeo-location data of the user 112A between the times tx and ty.

In the example, the processor 234 further determines a speed of anactivity of the user 112A performed at the time tx or at the time ty.The processor 234 determines a speed of the user 112A between the timestx and ty. Further, in this example, the processor 234 calculates speedas a ratio of a distance between the geo-locations 2 and 1 and adifference between the times ty and tx. In this example, based on thespeed, the processor 226 determines an amount of time taken by the user112A to reach an entry of the location 2. A geo-location correspondingto the entry of the location 2 is obtained from the device locator 222by the processor 234 and/or an amount of movement corresponding to theentry of the location 2 is obtained from the position sensor 220 of themonitoring device 108A, and the entry is determined from geo-location,the amount of movement, and/or the geo-location-location database by theprocessor 234. In this example, the processor 234 adds the amount oftime taken to reach the entry from the time tx to determine a time ofentry by the user 112A into the location 2 from the location 1.

It should be noted that the processor 234 of the monitoring device 108Aor the processor 226 of the computing device 166 determines geo-locationdata as located along a straight line between two boundaries. Forexample, geo-location data is located on a straight line 440 between theboundary A and the boundary B, geo-location data is located on astraight line 442 between the boundary B and the boundary C, andgeo-location data is located on a straight line 444 between a point 448and the boundary D.

In some embodiments, geo-location data is determined for minute timeintervals, e.g., times between the times tx and ty, every minute, everyfraction of a minute, etc., is compared to the geo-location data on astraight line between two boundaries or between a boundary and a point.The processor 234 or the processor 226 performs the comparison. Thegeo-location data determined for the minute time intervals may bedecimated by the processor 234 or the processor 226. The processor 234or the processor 226 determines whether a divergence between thegeo-location data obtained at the minute time intervals and geo-locationdata on a straight line between two boundaries exceeds a value. Upondetermining that the divergence exceeds the value, the processor 234 orthe processor 226 determines that there is a boundary at a point of thedivergence.

For example, a divergence between geo-location data on the straight line440 and geo-location data, obtained at minute time intervals, on a curve446 exceeds a value. In this example, the boundary A exists at a pointof the divergence. On the other hand, upon determining that thedivergence does not exceed the value, the processor 234 or the processor226 determines that there is no boundary at the point of lack ofdivergence. For example, a divergence between geo-location data on thestraight line 444 and geo-location data, obtained at minute timeintervals, on a straight line 446 does not exceed the value. In thisexample, there is no boundary formed at the point 448 at which the lines444 and 446 start to intersect.

FIG. 7D is a diagram of a GUI 460 to illustrate a method of allowing auser to choose a location in case of common geo-locations betweenmultiple locations. The GUI 460 is generated by executing the method 221(FIG. 6F). As shown in the GUI 460, the processor 234 or the processor226 determines that a location 462 and a location 464 has one or morecommon geo-locations 466. The locations 462 and 464 may be determined bythe processor 226 or the processor 234 based on thegeo-location-location database. The processor 234 generates a prompt anddisplays the prompt via the display device 276 (FIG. 3A) to the user112A. Similarly, the processor 226 generates the prompt to display viathe display device 352 (FIG. 5). The prompt indicates to the user 112Ato select the location 462 or the location 464 as a locationcorresponding to the geo-locations 466. The user 112 selects via theuser interface 274 (FIG. 3A) or via the input device 340 (FIG. 5) thelocation 462 or the location 464 as corresponding to the geo-locations466. Upon receiving the selection of the location 462 or the location464, the processor 226 or the processor 234 associates the selectedlocation to correspond to the geo-locations 466.

In some embodiments, the user 112A expands a size of the location 462via the user interface 274 (FIG. 3A) to indicate to include one or moregeo-locations within the location 466 to indicate to the processor 226that the one or more geo-locations within the location 466 are withinthe location 462. The processor 226 then associates the one or moregeo-locations with the location 462 instead of with the location 466.

In various embodiments, one or more geo-locations are located outsidethe location 466. The user 112A expands a size of the location 462 viathe user interface 274 (FIG. 3A) to indicate to include the one or moregeo-locations to indicate to the processor 226 that the one or moregeo-locations are within the location 462. The processor 226 thenassociates the one or more geo-locations with the location 462.

FIG. 7E is a diagram of an embodiment of a web page 470 that includesthe GUI 394 that further includes the events 128 ₁, 128 ₂, 128 ₃, 128 ₄,128 ₅, and 128 ₆. The GUI 394 is similar to the GUI 370 (FIG. 7A) exceptthat the GUI 394 is displayed within the web page 470 and the GUI 394includes a time 337 of exit by the user 112A of his/her home. In someembodiments, the GUI 394 includes a time of entry or exit by the user112A of a location.

A web page is displayed when the wireless communication device 278 (FIG.3A) or a wired communication device of the monitoring device 108A sendsa request for the web page to the server 228 via the network 176 withoutusing the computing device 166 (FIG. 3A). In some embodiments, therequest for a web page is sent from the NIC 356 of the computing device166 via the network 176 to the server 228.

Upon receiving the request for a web page, the server 228 sends the webpage via the network 176 to the computing device 166. The NIC 356 of thecomputing device receives a web page and the web page is displayed onthe display device 352 (FIG. 5) of the computing device 166.

Similarly, in some embodiments, upon receiving the request for a webpage, the server 228 sends the web page via the network 176 to themonitoring device 108A. The wireless communication device 278 (FIG. 3A)or a wired communication device of the monitoring device 108A receives aweb page and the web page is displayed on the display device 276 (FIG.3A) of the monitoring device 108A.

FIGS. 7F-1 and 7F-2 are diagrams used to illustrate an embodiment of azoom-in 496 of a portion 502 of a GUI 498. The GUI 496 is generated byexecuting the method 102 (FIG. 6A), 160 (FIG. 6B), 170 (FIG. 6C), or 210(FIG. 6E). In some embodiments, the zoom-in 496 is displayed on thedisplay device 276 (FIG. 3A) of the monitoring device 108A or on thedisplay device 352 (FIG. 5) of the computing device 166. The zoom-in 496is displayed when the user 112A selects the portion 502 via the userinterface 274 (FIG. 3A) or via the input device 340 (FIG. 5).

FIGS. 7G-1, 7G-2, and 7G-3 are diagrams used to illustrate an embodimentof a daily journal GUI 510. The daily journal GUI 510 is generated whenthe processor 234 or the processor 226 combines one or more GUIs 512,514, 516, and 518. Each GUI 512, 514, 516, and 518 is generated byexecuting the method 102 (FIG. 6A), 160 (FIG. 6B), 170 (FIG. 6C), or 210(FIG. 6E). The GUIs 512, 514, 516, and 518 have chronologically-ordereddates of one or more activities performed by the user 112A at one ormore locations over one or more periods of time. In some embodiments,the GUIs 512, 514, 516, and 518 have consecutive dates, which are datesof activities performed by the user 112A. The daily journal GUI 510 isdisplayed by the processor 234 on the display device 276 (FIG. 3A) ofthe monitoring device 108A or is displayed by the processor 226 on thedisplay device 352 (FIG. 5) of the computing device 166.

Each GUI 512, 514, 516, and 518 is displayed in a row. In someembodiments, each GUI 512, 514, 516, and 518 is displayed in a column orparallel to an oblique line.

FIG. 7H is a diagram of an embodiment of a daily journal GUI 520. Thedaily journal GUI 520 is generated when the processor 234 or theprocessor 226 combines one or more GUIs 522, 524, 526, and 528. Each GUI522, 524, 526, and 528 is generated by executing the method 102 (FIG.6A), 160 (FIG. 6B), 170 (FIG. 6C), or 210 (FIG. 6E). The GUIs 522, 524,526, and 528 have chronologically-ordered dates of one or moreactivities performed by the user 112A at one or more locations over oneor more periods of time. In some embodiments, the GUIs 522, 524, 526,and 528 have consecutive dates, which are dates of activities performedby the user 112A. The daily journal GUI 520 is displayed by theprocessor 234 on the display device 276 (FIG. 3A) of the monitoringdevice 108A or is displayed by the processor 226 on the display device352 (FIG. 5) of the computing device 166.

Each GUI 522, 524, 526, and 528 is displayed in an orderly fashion.

FIG. 7I is a diagram of an embodiment of a GUI 530 that provides anoverview of one or more activities 538 performed by the user 112A at oneor more locations 540 over a period of time. The activities 538 aregraphical elements. Similarly, the locations 540 are graphical elements.The GUI 530 is generated by executing the method 102 (FIG. 6A), 160(FIG. 6B), 170 (FIG. 6C), or 210 (FIG. 6E). The GUI 530 also includes atime line 542 that shows a relationship of time periods, e.g., a nighttime period, a day time period, etc., with performance of the activities538 and the locations 540. The activities 538, the locations 540, andthe time line 542 are aligned with respect to each other along a column550. The locations 540 include one or more location/activity identifiers544 ₁, 544 ₂, 544 ₃, and 544 ₄.

The activities 538 include a sedentary activity 546 ₁, a sedentaryactivity 546 ₂, a sedentary activity 546 ₃, a sedentary activity 546 ₄,a sedentary activity 546 ₄, a sedentary activity 546 ₅, a sedentaryactivity 546 ₆, a sedentary activity 546 ₇, and a sedentary activity 546₈. The activities 538 further include a lightly active activity 536 ₁, alightly active activity 536 ₂, a lightly active activity 536 ₃, alightly active activity 536 ₄, a lightly active activity 536 ₅, alightly active activity 536 ₆, and a lightly active activity 536 ₇. Theactivities 538 further includes a moderately active activity 534 ₁, amoderately active activity 534 ₂, a moderately active activity 534 ₃,and a highly active activity 532.

It should be noted that an activity level of the sedentary activeactivity is lower than an activity level of the lightly active activity.An activity level of the lightly active activity is lower than anactivity level of the moderately active activity and an activity levelof the moderately active activity is lower than an activity level of thehighly active activity. For example, a number of calories burned duringthe sedentary active activity is lower than a number of calories burnedduring the lightly active activity, a number of calories burned duringthe lightly active activity is lower than a number of calories burnedduring the moderately active activity, and a number of calories burnedduring the moderately active activity is lower than a number of caloriesburned during the highly active activity. As another example, an amountof activity performed at the sedentary active activity is lower than anamount of activity performed at the lightly active activity, an amountof activity performed at the lightly active activity is lower than anamount of activity performed at the moderately active activity, and anamount of activity performed at the moderately active activity is lowerthan an amount of activity performed at the highly active activity.

Each activity is vertically aligned with a location. For example, thesedentary activity 546 ₁ is vertically aligned with the location 544 ₁.As another example, the lightly active activity 536 ₁ is verticallyaligned with the locations 544 ₁ and 544 ₂.

In some embodiments, when an activity is aligned, e.g., vertically,horizontally, etc. with a location, the activity is performed at thelocation. For example, the monitoring device 108A worn by the user 112Acaptures positions used to determine an activity performed within a homeof the user 112A.

Moreover, it should be noted that although four activities are shown inFIG. 7I, in some embodiments, any number of activities may be shown.Furthermore, in some embodiments, the activities 538, the locations 540,and the time line 542 are aligned with respect to each other along a rowinstead of the column 550. For example, each of the activities 538, thelocations 540, and the time line 542 are made vertical instead ofhorizontal to be aligned with respect to each other along a row.

A cursor 552 is displayed on the GUI 530 by the processor 226 or by theprocessor 234. When the user 112A uses the user interface 274 (FIG. 3A)or the input device 340 (FIG. 5) to point the cursor 552 to a portion ofthe activities 538 and selects the portion, a progressively detailed GUI560 is displayed. The GUI 560 is displayed in FIG. 7J.

FIG. 7J is a diagram of an embodiment of the GUI 560. The GUI 560 isgenerated by executing the method 102 (FIG. 6A), 160 (FIG. 6B), 170(FIG. 6C), or 210 (FIG. 6E). The GUI 560 includes a detailed view of theactivities 538 (FIG. 7I) The detailed view is shown as activities 580.For example, the GUI 560 includes a detailed view of each activity levelof the GUI 530 (FIG. 7I). To illustrate, the highly active activity 532(FIG. 7I) is detailed as one or more highly active activity levels 582 ₁and 582 ₂ of the activity. As another illustration, the sedentaryactivities 546 ₁ thru 546 ₈ are detailed as one or more sedentaryactivity levels 562 ₁, 562 ₂, 562 ₃, 562 ₄, 562 ₅, 562 ₆, 562 ₇, and 562₈. As yet another illustration, the lightly active activities 536 ₁ thru536 ₇ are detailed as one or more lightly active activity levels 564 ₁,564 ₂, 564 ₃, 564 ₄, 564 ₅, 564 ₆, 564 ₇, and 564 ₈. As anotherillustration, the moderately active activities 534 ₁ thru 534 ₃ aredetailed as one or more moderately active activity levels 566 ₁, 566 ₂,566 ₃, and 566 ₄. In some embodiments the activities 580 are graphicalelements.

In some embodiments, each location/activity identifier of the GUI 530 isdetailed by the processor 226 or by the processor 234 into a detailedlocation/activity identifier within the GUI 560. For example, a buildingidentifier within the GUI 530 is detailed, within the GUI 560 into oneor more rooms of the building when the user 112A uses the user interface274 (FIG. 3A) or the input device 340 (FIG. 5) to point the cursor 552to a portion of the locations 540 (FIG. 7I) and to select the portion.

In various embodiments, the GUI 560 includes a detailed view, whichincludes one or more activity levels, of an activity of the GUI 530. Theactivity of the GUI 530 is one at which the user 112A points to andselects with the pointer 552. In some embodiments, the GUI 560 includesa detailed location/activity identifier of a location/activityidentifier, on the GUI 530, at which the user 112A points to and selectswith the pointer 552.

FIG. 7K is a diagram of an embodiment of the GUI 574. The GUI 574 is thesame as the GUI 560 (FIG. 7J) except that the GUI 574 shows a moredetailed view of one or more activities performed by the user 112A, of atime period during which the activities are performed, and/or of alocation at which the activities are performed, compared to that shownin the GUI 560. For example, when the user 112A uses the user interface274 (FIG. 3A) or the input device 340 (FIG. 5) to point the cursor 552to a portion, e.g., an activity level 582 ₁ (FIG. 7J), etc., of theactivities 580 (FIG. 7J) and to select the portion, a detailed view ofthe portion is displayed within the GUI 574. To illustrate, the detailedview of the portion includes a graphical element 588 that displays atime at which the activity level 582 ₁ occurs, a location/activityidentifier 590 identifying an activity, e.g., walking, running, etc.,performed at a location by the user 112A. The activity level 582 ₁ andan activity level 582 ₂ are portions of an activity level 582.

The detailed view further includes text 592 that describes the activity,having the activity level 582 ₁, performed by the user 112A, time ofoccurrence of the activity, and activity data, e.g., number of steps,calories burned, etc., of the activity. The detailed view furtherincludes a location/activity identifier 594 that represents a locationclosest to a location of performance of the activity identified by thelocation/activity identifier 590. For example, the location/activityidentifier 594 is a home icon of a home of the user 112A and the home isat a location closest to a location where the user 112A walks a dog. Thedetailed view further includes text 596 describing a location identifiedby the location/activity identifier 594. The graphical element 588, thelocation/activity identifier 590, and the location/activity identifier594 are aligned along a line 598. In some embodiments, the graphicalelement 588, the location/activity identifier 590, and thelocation/activity identifier 594 are not aligned with respect to eachother. In various embodiments, the detailed view excludes the text 592and/or excludes the text 596. In several embodiments, the detailed viewexcludes the location/activity identifier 590 and/or excludes thelocation/activity identifier 596. The GUI 574 is generated by executingthe method 102 (FIG. 6A), 160 (FIG. 6B), 170 (FIG. 6C), or 210 (FIG.6E).

FIG. 7L is a diagram illustrating an embodiment of a method of combiningactivity levels over a period of time. The method of combining activitylevels over a period of time is performed by the processor 226 or by theprocessor 234. In the method of combining activity levels, a GUI 602 isdisplayed by the processor 226 or by the processor 234.

The GUI 602 includes a display 604 ₁ of activity levels of a number ofactivities, e.g., an activity 1, an activity 2, and an activity 3, etc.performed by the user 112A during a day 1. The activities shown in thedisplay 604 ₁ are performed in the order shown. For example, theactivity 1 is performed during the day 1 before the activity 2 isperformed during the day 1 and the activity 2 is performed during theday 1 before the activity 3 is performed during the day 1.

Moreover, the GUI 602 includes a display 604 ₂ of activity levels of anumber of activities, e.g., an activity 2, an activity 1, and anactivity 3, etc. performed by the user 112A during a day 2. Theactivities shown in the display 604 ₂ are performed in the order shown.For example, the activity 2 is performed during the day 2 before theactivity 1 is performed during the day 2 and the activity 1 is performedduring the day 2 before the activity 3 is performed during the day 2.

The user 112A uses the user interface 274 (FIG. 3A) or the input device340 (FIG. 5) to point the cursor 552 to the activity 1 performed duringthe day 1 to select the activity 1 performed during the day 1 and dragthe activity 1 performed during the day 1 to a GUI 606, which is anactivity filter. The user 112A then uses the user interface 274 (FIG.3A) or the input device 340 (FIG. 5) to point the cursor 552 to theactivity 1 performed during the day 2 to select the activity 1 performedduring the day 2 and drag the activity 1 performed during the day 2 tothe GUI 606. In some embodiments, the processor 226 or the processor 234receives a selection from the user 112A via the user interface 274 (FIG.3A) or the input device 340 (FIG. 5) of the activity 1, the activity 2,or the activity 3 over a period of time, e.g., day 1, day 2, etc.,within the GUI 602 and the processor 234 drags the activities performedduring the period of time to present in the GUI 606.

When the user 112A uses the user interface 274 (FIG. 3A) or the inputdevice 340 (FIG. 5) to point the cursor 552 to the activity 1 performedduring the day 1 within the GUI 606 and selects the activity 1 performedduring the day 1 or to point the cursor 552 to the activity 1 performedduring the day 2 and selects the activity 1 performed during the day 2within the GUI 606, a GUI 608 is generated and displayed. The GUI 608includes an aggregate, e.g., total, etc., activity level 609 of theactivity 1 performed during the day 1 and includes an aggregate activitylevel 610 of the activity 1 performed during the day 2. Any aggregationof activity levels is performed by the processor 226 or by the processor234.

In some embodiments, upon receiving the selection of the activity 1, theactivity 2, or the activity 3 over a period of time, e.g., day 1, day 2,etc., within the GUI 602, the processor 226 or the processor 234generates a GUI, e.g., the GUI 608, having aggregate activity levels ofthe activity over the period of time for which the activity is selected.

FIG. 7M is a diagram of an embodiment of a GUI 614 that describes anaggregate level of one or more activities performed by the user 112Aover a period of time. The processor 226 or the processor 234 determinesan aggregate amount of an activity performed by the user 112A over aperiod of time. The processor 234 or the processor 234 generates asimplified description of the aggregate amount of the activity anddisplays the simplified description on a corresponding display device.For example, when the user 112A selects a tab 616 via the user interface274 (FIG. 3A) or the input device 340 (FIG. 5), simplified descriptions620, 622, and 624 are displayed within the GUI 614 for one or moreperiods of time. The simplified description 620 is of activitiesperformed by the user 112A on Thursday, March 1, the simplifieddescription 622 is of activities performed by the user 112A on Friday,March 2, and the simplified description 624 is of activities performedby the user 112A on Saturday, March 3.

Each simplified description of activities performed during a period oftime is displayed besides a corresponding sequence of events occurringduring the period of time. For example, the simplified description 620of activities performed on Thursday, March 1 is displayed besides one ormore events 626 occurring on Thursday, March 1.

FIG. 7N is a diagram of an embodiment of a pie-chart 650 of locations atwhich the user 112A performs one or more activities and of percentagesof activity levels at the locations over a period of time. The period oftime is represented by the pie-chart 650. The pie-chart 650 is generatedby the processor 226 or the processor 234.

The pie-chart 650 is segmented into a location 652, a location 654, alocation 656, an activity 658, an activity 660, an activity 662, and alocation/activity 664. When the user 112A is at the location 652, theuser 112A has an activity level of 666. Similarly, when the user 112A isat the location 654, the user 112A has an activity level of 668. Whenthe user 112A is at the location 656, the user 112A has an activitylevel of 670. Moreover, when the user 112A is performing the activity658, the user 112A has an activity level of 672. When the user 112A isperforming the activity 660, the user 112A has an activity level of 674.Also, when the user 112A is performing the activity 662, the user 112Ahas an activity level of 676. When the user 112A is performing theactivity 664 or is at the location 664, the user 112A has an activitylevel of 678.

In some embodiments, an activity level of an activity performed at alocation by the user 112A is determined by the processor 226 or theprocessor 234 in terms of a percentage of an amount of activity thatwould have been performed at the location. For example, the processor226 or 234 determines that a maximum amount of activity that can beperformed by the user 112A or any other user at the location 652 is n.The processor 226 or 234 receives an amount of activity actuallyperformed by the user 112A as m. The processor 226 or 234 determines apercentage (m/n)×100 as the activity level 666.

In various embodiments, any other type of graph, e.g., a bar graph, aline graph, etc., is generated by the processor 226 or the processor 234instead of a pie chart.

FIG. 7O is a diagram of an embodiment of a GUI 690 that includes anoverlay of a map 692 on one or more locations 696, 698, and 700 that theuser 112A visits during a period of time to perform one or moreactivities 701, 702, 704, and 708 performed by the user 112A during theperiod of time. The GUI 690 is generated by the processor 226 or by theprocessor 234. The GUI 690 is generated by executing the method 221(FIG. 6F).

The GUI 690 includes a map 692 of a path traveled by the user 112Aduring a period of time, text describing the locations 696, 698, and 700and text describing the activities 701, 702, 704, and 708.

In some embodiments, instead of text describing the locations 696, 698,and 700, one or more graphical elements or a combination of thegraphical elements and text describing the locations are used within theGUI 690 to indicate the locations. In various embodiments, instead oftext describing the activities 701, 702, 704, and 708, one or moregraphical elements or a combination of the graphical elements and textdescribing the activities are used within the GUI 690 to indicate theactivities.

In a number of embodiments, the one or more locations 696, 698, and 700are overlaid on the map 692.

FIG. 7P is a diagram of an embodiment of a web page 714 that illustratesthat a map 732 is overlaid on the event region 730 to indicate ageo-location of the user 112A at a time, e.g., an hour, a minute, etc.,within a time period in which the user 112A performs one or moreactivities. The web page 714 includes a GUI 716 that further includesthe map 732 and the event region 730. When the user 112A selects a time,e.g., 11 AM, NOON, 1 PM, etc., on the GUI 370 (FIG. 7A) via the userinterface 274 (FIG. 3A) or the input device 340 (FIG. 5), a map, e.g.,the map 732, etc., is overlaid by the processor 226 or the processor 234on the GUI 370 to indicate a geo-location of the user 112A at the time.For example, the geo-location is indicated by centering the map at thegeo-location of the user 112A at the time.

The GUI 716 is generated by executing the method 102 (FIG. 6A), 160(FIG. 6B), 170 (FIG. 6C), or 210 (FIG. 6E) in combination with themethod 221 (FIG. 6F).

In some embodiments, the event region 730 is overlaid on the map 732.

FIG. 7Q is a diagram of an embodiment of a GUI 750 that includes a map752 below an event region 754. The GUI 750 is generated by the processor226 or the processor 234. The event region 754 includes one or morelocation/activity identifiers 754 ₁, 754 ₂, 754 ₃, 754 ₄, 754 ₅, and 754₆ of locations visited by the user 112A during a period of time.Moreover, the event region 754 includes graphical elements and/or textthat represent one or more activities 756 ₁, 756 ₂, 756 ₃, 756 ₄, and756 ₅ performed by the user 112A during the period of time.

The GUI 750 further includes links 758 ₁, 758 ₂, 758 ₃, 758 ₄, 758 ₅,758 ₆, 758 ₇, 758 ₈, and 758 ₉ between a set including one or moregeo-locations 760 ₁, one or more geo-locations 760 ₂, one or moregeo-locations 760 ₃, one or more geo-locations 760 ₄, one or moregeo-locations 760 ₅, and one or more geo-locations 760 ₆ on the map 752and a set including one or more of the location/activity identifiers 754₁, 754 ₂, 754 ₃, 754 ₄, 754 ₅, and 754 ₆ and/or one or more of theactivities 756 ₁, 756 ₂, 756 ₃, 756 ₄, and 756 ₅. For example, the link758 ₁ is established between the one or more geo-locations 760 ₁ and thelocation 754 ₁.

The GUI 750 is generated by executing the method 102 (FIG. 6A), 160(FIG. 6B), 170 (FIG. 6C), or 210 (FIG. 6E) in combination with themethod 221 (FIG. 6F).

In some embodiments, a geo-location is represented as a graphicalelement and/or as text by the processor 226 or by the processor 234.

In some embodiments, the map 752 is placed by the processor 236 or theprocessor 234 at any other place, e.g., above, to the left of, to theright of, etc., with respect to the event region 754.

FIG. 7R is a diagram of an embodiment of a web page 770 that is used toillustrate an overlay of event data on a map 774. A map is accessed bythe processor 234 of the monitoring device 108A via the wirelesscommunication device 278 (FIG. 3A) or a wired communication device ofthe monitoring device 108A and the network 176 (FIG. 3A) from thegeo-location-location database of the server 228 (FIG. 3A) or anotherserver without using the computing device 166 (FIG. 3A). In someembodiments, the map 774 is accessed by the processor 234 of themonitoring device 108A via the wireless communication device 278 (FIG.3A) or a wired communication device of the monitoring device 108A, thecomputing device 166, and the network 176 (FIG. 3A) from thegeo-location-location database of the server 228 (FIG. 3A) or anotherserver. In a number of embodiments, the map 774 is accessed by theprocessor 226 of the computing device 166 via the NIC 356 (FIG. 5) ofthe computing device 166 and via the network 176 (FIG. 3A) from thegeo-location-location database of the server 228 (FIG. 3A) or anotherserver.

The web page 770 includes a GUI 772 that is displayed by the processor226 or the processor 234. The GUI 772 is generated by the processor 226or the processor 234. The GUI 772 is generated by executing the method102 (FIG. 6A), 160 (FIG. 6B), 170 (FIG. 6C), or 210 (FIG. 6E) incombination with the method 221 (FIG. 6F).

The map 774 includes one or more geo-locations, names of landmarksaccessed from the geo-location-location database, names of public placesaccessed from the geo-location-location database, names of streetsaccessed from the geo-location-location database, names of geo-locationsaccessed from the geo-location-location database, or a combinationthereof, etc.

The event data is overlaid on the map 774 by the processor 226 or by theprocessor 234. The event data includes one or more of alocation/activity identifier 776 ₁, e.g., a home identifier, etc., alocation/activity identifier 776 ₂, e.g., an identifier of a bus, etc.,a location/activity identifier 776 ₃, e.g., an identifier of a railwaystation, etc., a location/activity identifier 776 ₄, e.g., a vehicleidentifier, etc., a location/activity identifier 776 ₅, e.g., a worklocation/activity identifier, etc., of locations visited by the user112A during a period of time and an activity identifier 778 ₁ of anactivity, e.g., walking, etc., performed by the user 112A during theperiod of time. The event data further includes a path 780 taken by theuser 112A during the period of time in visiting the locations having thelocation/activity identifiers 776 ₁, 776 ₂, 776 ₃, 776 ₄, and 776 ₅ andin performing an activity, e.g., walking, etc., represented by theactivity identifier 778 ₁.

In some embodiments, the event data includes activity data of any numberof activities performed by the user 112A.

In several embodiments, the map 774 is overlaid on the event data.

In various embodiments, the activity identifier 778 ₁, the path 780,and/or the location/activity identifiers 776 ₁, 776 ₂, 776 ₃, 776 ₄, and776 ₅ are color-coded by the processor 226 or the processor 234. Forexample, the processor 226 or the processor 234 assigns a differentcolor to the identifier 778 ₁ than to one or more of thelocation/activity identifiers 776 ₁, 776 ₂, 776 ₃, 776 ₄, and 776 ₅, andthe path 780. As another example, the processor 226 or the processor 234assigns a different color to the location/activity identifier 776 ₁ thanto one or more of the location/activity identifiers 776 ₂, 776 ₃, 776 ₄,and 776 ₅. As another example, the processor 226 or the processor 234assigns a different color to the path 780 than to one or more of thelocation/activity identifiers 776 ₁, 776 ₂, 776 ₃, 776 ₄, and 776 ₅

In some embodiments, the activity identifier 778 ₁, the path 780, and/orthe location/activity identifiers 776 ₁, 776 ₂, 776 ₃, 776 ₄, and 776 ₅are coded by the processor 226 or the processor 234 by using graphicalproperties. For example, the processor 226 or the processor 234 assignsa different graphical property to the activity identifier 778 ₁ than toone or more of the location/activity identifiers 776 ₁, 776 ₂, 776 ₃,776 ₄, and 776 ₅, and the path 780. As another example, the processor226 or the processor 234 assigns a different graphical property to thelocation/activity identifier 776 ₁ than to one or more of thelocation/activity identifiers 776 ₂, 776 ₃, 776 ₄, and 776 ₅. As anotherexample, the processor 226 or the processor 234 assigns a differentgraphical property to the path 780 than to one or more of thelocation/activity identifiers 776 ₁, 776 ₂, 776 ₃, 776 ₄, and 776 ₅

FIG. 7S is a diagram of an embodiment of the web page 770 that is usedto illustrate a zoom-in 790 of a portion of the map 774 and of eventdata of an event that occurs at the portion. When the user 112A uses theuses the user interface 274 (FIG. 3A) or the input device 340 (FIG. 5)to point the cursor 552 to the activity identifier 778 ₁, the processor226 or the processor 234 generates the zoom-in 790 to display thezoom-in 790. In some embodiments, a zoom-in is an example of a GUI.

The zoom-in 790 includes a detailed display 792 associated with theactivity identifier 778 ₁ of an activity performed by the user 112A atone or more geo-locations close to, e.g., within a vicinity of, within aradius of, etc., a location having the location/activity identifier 776₅. The detailed display 792 includes a distance traveled by the user112A close to a location having the location/activity identifier 776 ₅,a number of steps taken by the user 112A close to the location, and atextual description of an activity that is identified by the activityidentifier 778 ₁ and that is close to, e.g., with a radius of, etc., thelocation.

In some embodiments, the zoom-in 790 includes any other activity data,e.g., a number of calories burned by the user 112A close to a locationhaving the location/activity identifier 776 ₅, an amount of golf swingstaken by the user 112A close to the location, etc.

FIG. 7T is a diagram of an embodiment of a web page 751 that includes aGUI 759. The GUI 759 includes an overlay of a map 753 on a user's path755. The user's path 755 is a path traveled by the user 112A during aperiod of time. The user's path 755 is coded to distinguish variouslocations and/or activities along the user's path 755. For example, abus station is provided a different color by the processor 234 or by theprocessor 226 than that provided to a railway station. As anotherexample, a walking activity of the user 112A along the user's path 755is provided a different shade, text, and/or color by the processor 234or by the processor 226 than that provided to a running activity of theuser 112A along the user's path 755. The GUI 759 is generated byexecuting the method 102 (FIG. 6A), 160 (FIG. 6B), 170 (FIG. 6C), or 210(FIG. 6E) in combination with the method 221 (FIG. 6F).

In some embodiments, the user's path 755 is overlaid on the map 753.

FIG. 7U is a diagram of an embodiment of a zoom-in 757 that includes azoom-in of a portion of the user's path 755. The zoom-in 757 isgenerated when the user 112A points the cursor 552 (FIG. 7I) on aportion of the user's path 755 and selects the portion. The zoom-in 757is of the portion of the user's path 755. The zoom-in 757 includesactivity data, e.g., number of steps walked by the user 112A within theportion, a distance covered by the user 112A within the portion, and atype of activity, e.g., walking, running, etc., performed by the user112A within the portion.

FIG. 7V is a diagram of an embodiment of the GUI 759 except that the GUI759 indicates that a portion of the user's path 758 at which the user112A takes bus to a train is coded differently than a portion of theuser's path 758 at which the user 112A is traveling to work on a trainand differently than a portion of the user's path 758 where the user112A is walking around near his/her office.

FIG. 8 is a diagram of an embodiment of one or more location/activityidentifiers 802 ₁, 802 ₂, and 802 ₃, and one or more activityidentifiers 804 ₁, 804 ₂, and 804 ₃. Each identifier 802 ₁, 802 ₂, 802₃, 804 ₁, 804 ₂, and 804 ₃ includes a pointer. For example, theidentifier 802 ₁ includes a pointer 806. In some embodiments, eachidentifier excludes a pointer.

FIG. 9A is a flowchart of an embodiment of a method 850 for generating arecommendation to help the user 112A achieve a goal. The method 850 isexecuted by the server 228 or by the computing device 166.

The method 850 includes an operation 852 of receiving a goal for theuser account 174 (FIG. 2A). Examples of a goal include achieving anactivity level of one or more activities within an amount of time. Toillustrate, a goal may be to achieve a number of calories burned withina week. To further illustrate, a goal may be to achieve an amount ofweight loss within a month. As another illustration, a goal may be torun or walk a number of steps every day. As another example, a goalincludes achieving an activity level of one or more activities at one ormore locations within an amount of time. As yet another example, a goalincludes achieving an activity level of one or more activities at one ormore locations.

Other examples of a goal include achieving an activity level at alocation within an amount of time. To illustrate, a goal may be to walka number of steps at work each day. As another illustration, a goal maybe to go to bed at 9 PM at home each night.

Other examples of a goal include a goal G1 shown below in FIG. 11A, agoal G2 shown below in FIG. 11B, a goal G3 shown below in FIG. 11C, anda goal G4 shown below in FIG. 11D.

In some embodiments, a goal is associated with an activity that istrackable via a monitoring device. For example, a goal is to walk anumber of steps, which is trackable by the position sensor or the devicelocator of a monitoring device. As another example, a goal is to walk ata geo-location for an amount of time and the goal is trackable by thedevice locator and the time measurement device of a monitoring device.

A goal is provided by the user 112A via the user interface of amonitoring device or via the input device of the computing device 166.For example, the user 112A logs into a representation of the useraccount 174 to provide the goal.

A goal is received from the NIC of the computing device 166 and thenetwork 176 by the NIC of the server 228. In some embodiments, a goal isreceived from a communication device, e.g., wireless communicationdevice, wired communication device, etc., of a monitoring device via thenetwork 176 by the NIC of the server 228. In various embodiments, a goalis received by the processor of the computing device 166 from the inputdevice of the computing device 166.

In some embodiments, the goal is received by a communication device ofthe computing device 166 from a communication device of a monitoringdevice.

It should be noted that several communications, e.g., reception, etc.,are described herein as being performed by the NIC of the server 228. Insome embodiments, the communications may be performed between acommunication device of a monitoring device and a communication deviceof the computing device 166. For example, the goal that is described asreceived by the NIC of the server 228 may be received from acommunication device of a monitoring device by a communication device ofthe computing device 166.

In a number of embodiments, a goal is set by the processor of the server228, the processor of a monitoring device, or by a processor of thecomputing device 166. For example, a processor analyzes past activitylevels of the user 112A and determines the goal to facilitate anincrease or decrease in the activity levels.

The method 850 further includes an operation 854 of receiving trackingdata associated with a monitoring device. The tracking data isassociated with a monitoring device when the tracking data includes oneor more positions, e.g., the position A, B, C, D, (FIGS. 1B, 1C), etc.,of a monitoring device that sends the tracking data. For example, thetracking data includes a position with respect to the xyz co-ordinatesystem of the monitoring device 108A that sends the tracking data. Asanother example, the tracking data includes an amount of movement of amonitoring device.

At least a part of the tracking data is associated with an activity. Forexample, the user 112A performs an activity to allow the position sensorof a monitoring device to generate the tracking data.

The operation 854 is performed by the NIC of the server 228 or thecomputing device 166. For example, the tracking data is received fromthe NIC of the computing device 166 and the network 176 by the NIC ofthe server 228. In some embodiments, the tracking data is received froma communication device, e.g., wireless communication device, wiredcommunication device, etc., of a monitoring device via the network 176by the NIC of the server 228. In various embodiments, the tracking datais received by the processor of the computing device 166 from the inputdevice of the computing device 166. In some embodiments, the trackingdata is received by a communication device of the computing device 166from a communication device of a monitoring device.

The method 850 includes an operation 856 of receiving geo-location dataassociated with a monitoring device. The geo-location data is associatedwith a monitoring device when the geo-location data includes one or moregeo-locations of a monitoring device that sends the geo-location data.

The geo-location data is correlated to the tracking data. For example,the geo-location data includes a latitude and a longitude of the user112A when the user 112A is performing an activity used to generate thetracking data.

The operation 856 is performed by the NIC of the server 228 or by thecomputing device 166. For example, the geo-location data is receivedfrom the NIC of the computing device 166 and the network 176 by the NICof the server 228. In some embodiments, the geo-location data isreceived from a communication device, e.g., wireless communicationdevice, wired communication device, etc., of a monitoring device via thenetwork 176 by the NIC of the server 228. In various embodiments, thegeo-location data is received by the processor of the computing device166 from the input device of the computing device 166. In someembodiments, the geo-location data is received by a communication deviceof the computing device 166 from a communication device of a monitoringdevice.

The method 850 includes an operation 858 of analyzing the receivedtracking data and geo-location data to characterize a currentperformance metric, e.g., an activity level, etc., for an activity. Forexample, the tracking data and the geo-location data is used todetermine the current performance metric. To illustrate, an activitylevel of the user 112A for one or more time periods is calculated andthe activity level is the current performance metric. To illustrate, anactivity level of one or more activities performed by the user 112A forone or more time periods at one or more locations is calculated and theactivity level is the current performance metric. To further illustrate,a number of steps taken by the user 112A during a day is determined andthe number is the current performance metric. As another illustration,an amount of time spent by the user 112A in a vehicle during a day iscalculated and the amount is the current performance metric. As yetanother illustration, a sum of activity levels of one or more activitiesperformed by the user 112A at one or more locations is calculated andthe sum is the current performance metric.

The operation 858 is performed by the processor of a monitoring device,or the processor of the computing device 166, or the processor of theserver 228.

The method 850 includes an operation 860 of generating a recommendationfor the user account 174. For example, upon determining that the currentperformance metric will not help the user 112A achieve a goal, arecommendation to perform an activity to achieve the goal is generated.As another example, upon determining that the current performance metricwill not help the user 112A achieve a goal, a recommendation to performan activity at a location is generated to help the user 112A achieve thegoal. As yet another example, upon determining that the user 112A hasnot achieved a milestone of being active for more than two hours in arow on contiguous days, the user 112A is recommended to take a walkaround his place of work, or get a drink, or move, etc. As anotherexample, upon determining the user 112A has spent more than a number ofhours in his vehicle on a commute to a parking place and walks less thana number of steps from the parking place to work, it is recommended tothe user 112A to park away even further away from work and walk morethan the number of steps to work. As another example, when it isdetermined that the user 112A is at work for more than 10 hours a day, apositive, caring reminder is generated to take a break for a fewminutes. As another example, when it is determined that the user 112Ahas a goal of improving his activity level at work and it is determinedthat the user 112A is sitting around for hours after lunch time, e.g.,12 PM, 1 PM, etc., a reminder of the goal is generated and sent to theuser account 174. As yet another example, when it is determined that theuser 112A has a goal to play golf in a week and it is determined thatsix days of the week has passed, a reminder to play golf is generated onthe sixth day or the seventh day of the week to the user account 174.

The activity recommended may be the same or different than the activitybased on which the current performance metric is generated. For example,the activity recommended is running and the activity used to generatethe current performance metric is walking. As another example, theactivity recommended is sleeping and the activity used to generate thecurrent performance metric is sleeping.

Similarly, the location recommended may be the same or different than alocation based on which the current performance metric is generated. Forexample, the location recommended may be a park and the location basedon which the current performance metric is generated is a work place. Asanother example, the location recommended is a gym and the locationbased on which the current performance metric is generated is a gym.

Examples of the recommendation generated in the operation 860 include arecommendation R7 (FIG. 14) and a recommendation R9 (FIG. 16).

In some embodiments, the recommendation generated in the operation 860includes the current performance metric and a suggested action andlocation for increasing the current performance metric to achieve thegoal. For example, the recommendation includes that the user 112A has anactivity level of 10,000 steps a day, a suggestion action of walking for2000 more steps a day at a park to achieve a goal of 360,000 steps permonth. As another example, the recommendation includes that the user112A has an activity level of waking up after 9 am and a suggestion ofwaking up at 8 am and walking achieve a goal of 400,000 steps per month.As another example, the recommendation includes that the user 112A hasan activity level of waking up after 9 am and a suggestion of waking upat 8 am and walking to achieve a goal of losing 10 pounds per month.

The operation 860 is performed by the processor of the server 228 or theprocessor of the computing device 166.

The recommendation generated is sent to a monitoring device for displayon the display device of the monitoring device. For example, therecommendation is sent from the NIC of the server 228 via the network176 to a communication device of a monitoring device.

In some embodiments, the recommendation generated is sent to thecomputing device 166 for display on the display device of the computingdevice 166. For example, the recommendation is sent from the NIC of theserver 228 via the network 176 to the NIC of the computing device 166.

In several embodiments, the recommendation generated is sent from acommunication device of the computing device 166 to a communicationdevice of a monitoring device.

FIG. 9B is a flowchart of an embodiment of a method 890 for generating arecommendation to help the user 112A achieve a goal. The method 890 isperformed by a monitoring device.

The method 890 includes an operation 852 of receiving a goal for theuser account 174. For example, the goal is received via the userinterface of the monitoring device 108A. To illustrate, the user 112Alogs into a representation of the user account 174 on the display deviceof a monitoring device and provides a goal to the representation.

The method 890 further includes an operation 892 of obtaining trackingdata associated with a monitoring device. The operation 892 is performedby the position sensor of a monitoring device.

The method 890 includes an operation 894 of obtaining geo-location dataassociated with a monitoring device. The operation 894 is performed bythe device locator of a monitoring device.

The method 890 includes the operations 858 and 860. The operations 858and 860 of the method 890 are performed by the processor of a monitoringdevice.

The recommendation generated in the operation 860 of the method 890 issent to the display device of a monitoring device for display.

In some embodiments, the method 850 (FIG. 9A) or the method 890 includesan operation of analyzing the tracking data and geo-location data tocompute whether milestones for the goal are reached. For example, it isdetermined whether a milestone of 15,000 steps a day is reached toachieve a goal of losing 10 pounds a month. As another example, it isdetermined whether a milestone of 100 tennis shots per day is reached toachieve a goal of losing a number of calories in a week. As anotherexample, it is determined whether the user 112A is sedentary for morethan two hours in a row on contiguous days. In this example, the user112A has not achieved a milestone of not being sedentary for more thantwo hours in a row on contiguous days.

In various embodiments, a milestone is a sub-goal for achieving a goal.For example, a milestone to achieve a goal of walking 360,000 steps amonth is to walk 12,000 steps a day. As another example, a milestone toachieve a goal of losing 5 pounds in a month is to run for 20 minutestoday.

In some embodiments, a milestone is a number of times an activity isperformed in a time period or a sum of one or more activity levels ofone or more activities performed by the user 112A in a time period. Forexample, a milestone includes a number of walks per time period, or anumber of runs per time period, or a number of times the user 112Abicycled per time period, or a number of times the user 112A went to agym per time period, or a length of time that the user 112A is at workper time period, or a length of time for which the user 112A sleptduring a time period, or a change in weight of the user 112A per timeperiod, a weight to be achieved at an end of a time period, a number ofcalories to be burned at an end of a time period, or a change incalories of the user 112A per time period, or a combination thereof.

In various embodiments, a milestone is associated with a subset of anamount of time in which a goal is to be achieved. For example, when agoal is to be achieved in a month, each milestone is to be achieved in aday or a week. As another example, when a goal is to be achieved in ayear, a milestone is to be achieved in a week, or a month, or sixmonths, or ten months, etc.

In some embodiments, a milestone is provided to the user account 174 tobe achieved each day, or each week, or each month, or each year to helpthe user 112A identify good and bad habits and to help achieve alifestyle change in the life of the user 112A.

In various embodiments, a reward is generated for the user account 174upon reaching one or more of the milestones or upon reaching a goal. Forexample, a badge is generated upon determining that the user 112A hasreached an activity level at a location. As another example, a badge isgenerated when the user 112A achieves a number of steps at a locationwithin a time period. The reward is generated by the processor of amonitoring device, the processor of the computing device 166, or theprocessor of the server 228. An example of the reward includes a badgeB1 (FIG. 11B). Other examples of a badge include a badge for walkingacross the golden gate bridge, or a “Forestry” badge for walking arounda park, or a badge for running a marathon, or a badge for walking for acure of a disease.

In some embodiments, each reward is location based and/or activitybased. For example, there is a different badge for climbing a portion ofMount Everest than that for winning a cycling race. The badge forclimbing the portion of Mount Everest has a different graphical elementthan that of the badge for winning the cycling race. As another example,there is a different badge for staying less at work than that forachieving a milestone of walking 20,000 steps in a day.

In some embodiments, the action and location suggested by executing theoperation 860 is defined to facilitate the action to increase thecurrent performance metric. For example, the action and location issuggested to increase a number of steps walked by the user 112A. Asanother example, the action and location is suggested to increase anactivity level of the user 112A. As yet another example, the action andlocation is suggested to increase an amount of calories burned by theuser 112A. As another example, the user 112A is recommended to walk at agolf course instead of playing golf. As another example, the user 112Ais suggested to walk at a park instead of walking at work.

In various embodiments, the action and locations are suggested byaccessing an action/location database of pre-associated actions andcorresponding locations. The action/location database is accessed toproduce a plurality of candidate actions and locations and to identify,from the candidate locations and actions, a suggested action and asuggested location that is customized for the user account 174. Forexample, it is determined that whether the action/location databaseincludes a stored location that is close, e.g., within a radius of,within a distance of, etc., to a location determined based on thegeo-location data. Upon determining that the stored location within theaction/location database is close to the determined location, the storedlocation is identified for the user account 174. As another example, itis determined whether the action/location database includes a storedactivity that will help the user 112A achieve the goal. Upon determiningthat the stored activity will help the user 112A achieve the goal, theactivity is identified to the user account 174. As yet another example,it is determined whether the action/location database includes a storedactivity and a stored location. It is further determined whether thestored location is close to the location determined based on thegeo-location data of the operations 856 (FIG. 9A) or 894 (FIG. 9B). Itis also determined whether the stored activity will increase the currentperformance metric of the user 112A to help the user achieve the goal.Upon determining that the stored location is close to the determinedlocation and that the stored activity will help the user 112A achievethe goal, the stored location and the stored activity are suggested tothe user account 174.

The operations of suggesting the action and locations, accessing theaction/location database of pre-associated actions and correspondinglocations, producing a plurality of candidate actions and locations, andidentifying the suggested action and location that is customized for theuser account 174 are performed by a processor. The processor may be theprocessor of a monitoring device, the processor of the computing device166, or the processor of the server 228.

The action/location database is a database of the memory device of theserver 228, of a virtual machine, or of a server within the network 176.

In some embodiments, the action/location database includes historicaltracked actions of the user 112A or of another user, e.g., the user112B, 112C, etc. For example, the user 112A may have achieved the goalby performing the action historically. When the same goal or anothergoal that is within a value of the goal is received by a processor,historical action is recommended to the user 112A via the user account174.

In various embodiments, the recommendation of the suggested action andlocation includes identifying an additional period of time to continuethe activity to achieve the goal. As an example, the recommendation ofthe suggested action and location includes identifying an additionalperiod of time to continue the activity to achieve the goal at alocation at which the user 112A is performing the activity. Toillustrate, it is recommended that the user 112A walk for an additionalten minutes in a park at a time the user 112A is walking in the park. Asanother illustration, it is recommended that the user 112A swing abaseball bat for an additional 50 times when the user 112A is in abaseball field practicing baseball. As yet another illustration, it isrecommended that the user 112A do yoga for 20 more minutes at a time theuser 112A is at a gym doing yoga.

The generation of the recommendation of the suggested action andlocation includes identifying an additional period of time to continuethe activity to achieve the goal is performed by a processor. Theprocessor may be the processor of a monitoring device, the processor ofthe computing device 166, or the processor of the server 228.

In several embodiments, the recommendation of the suggested action andlocation provides for suggestions to change a pattern of historicaltracked actions to achieve the goal. For example, it is recommended thatthe user 112A perform an activity different from an activity that theuser 112A has historically performed. To illustrate, it is determinedthat the user 112A run instead of walk. In this illustration, it isdetermined based on the geo-location data, the tracked data, and/or thegeo-location-location database that the user 112A has walkedhistorically. As another illustration, it is recommended that the user112A play a sport instead of being sedentary. In this illustration, itis determined based on the geo-location data, the tracked data, and/orthe geo-location-location database that the user 112A has been sedentaryhistorically.

In some embodiments, instead of the operation 805, it is determinedwhether there is a reduced likelihood that the milestone will beachieved. For example, a total activity level of the first activity toachieve the milestone in a remainder of a period of time is calculated.The period of time is allocated by a processor to achieve the milestone.It is determined whether the user 112A can perform the first activity toachieve the total activity level in the remainder of the time period.Upon determining that the user 112A cannot perform the first activity toachieve the total activity level, it is determined that there is thereduced likelihood that the milestone will be achieved. On the otherhand, upon determining that the user 112A can perform the first activityto achieve the total activity level in the remainder time period, it isdetermined that there is a likelihood that the milestone will beachieved.

In this example, a historical database that stores information regardingwhether the first activity is previously performed to achieve the totalactivity level in the remainder of the time period is accessed by aprocessor to determine whether the user 112A can perform the firstactivity to achieve the total activity level in the remaining timeperiod. The historical database is stored on the server 228 or on thenetwork 176 or on a virtual machine. The information regarding whetherthe first activity is previously performed to achieve the total activitylevel in the remainder time period includes activity levels of the firstactivity performed by the user 112 in the past or by other users, e.g.,the user 112B, the user 112C, etc. in the past.

As another example of determining whether there exists the reducedlikelihood that the milestone will be achieved, the historical databasethat stores information regarding whether the first activity ispreviously performed to achieve the total activity level at the firstlocation in the remainder of the time period is accessed by a processorto determine whether the user 112A can perform the first activity at thefirst location to achieve the total activity level in the remaining timeperiod. Upon determining that the user 112A cannot perform the firstactivity at the first location to achieve the total activity level inthe remainder time period, it is determined that there is the reducedlikelihood that the milestone will be achieved. On the other hand, upondetermining that the user 112A can perform the first activity at thefirst location to achieve the total activity level at the first locationin the remainder time period, it is determined that there is alikelihood that the milestone will be achieved. The first activity andthe first location stored in the historical database include the firstactivity performed by the user 112A in the past or by other users, e.g.,the user 112B, the user 112C, etc. in the past and further include thefirst location visited by the user 112A and/or the other users in thepast.

Moreover, in these embodiments, the operation 808 is performed when itis determined that there is the reduced likelihood and the operation 806is performed when it is determined the reduced likelihood does not existand that the milestone is achieved.

In a number of embodiments, the other users are assigned a different,e.g., higher, lower, etc., weight by a processor than that assigned tothe user 112A. For example, when the historical database indicates thatone of the other users has achieved a milestone in the past with thetotal activity level of the first activity performed at the firstlocation and the user 112A has not, the achievement of the milestone bythe other users is assigned a lower weight than a weight assigned to theuser 112A.

In some embodiments, the historically stored activities performed by theother users and/or the historically stored locations visited by theother users to achieve the total activity level in the remaining of thetime period are assigned a different weight by a processor than thatassigned to the user 112A based on whether the other users are similarto the user 112A. For example, it is determined by a processor whetherthe other users have similar demographics or dissimilar demographics asthat of the user 112A. To illustrate, the other users have a similardemographic when the other users have a demographic that is within arange of the demographic of the user 112A and the other users have adissimilar demographic when the other users have a demographic that isoutside the range. To further illustrate, when one of the other usershave an age of 20 years and the user 112A has an age of 22 years, theother user and the user 112A has a similar demographic. The number ofyears 22 is within a range 2 of the number of years 20. Upon determiningthat the other users are similar to the user 112A, the historicallystored activities performed by the other users and/or the historicallystored locations visited by the other users to achieve the totalactivity level in the remaining of the time period are assigned a higherweight than that provide when the other users are dissimilar to the user112A.

Examples of the reduced likelihood include less than 50% chance, or lessthan a 30% chance, or less than a 40% chance, or less than a 20% chance,or less than a 10% chance.

In some embodiments, instead of the historical database, a socialnetwork database of a computer social network is used. For example, itis determined whether the user 112A and/or his social network friendsare posting or commenting about the user 112A. To illustrate, the postor comment may include that the user 112A will not be able to achieve amilestone. As another illustration, the post of comment may include thatthe user 112A will be able to achieve the milestone.

In these embodiments, a statistical value, e.g., an average, a majority,a median, etc., is calculated by a processor based on the posts orcomments made by the user 112A and the posts or comments made by thesocial network friends. For example, it is determined whether a majorityof comments made by the user 112A and the social network friendsindicate that the user 112A will be able to achieve the milestone. Ifso, it is determined by a processor that there is a likelihood that theuser 112A will achieve the milestone. On the other hand, if the majorityof comments indicate that the user 112A will not be able to achieve themilestone, it is determined by a processor that there is the reducedlikelihood that the user 112A will achieve the milestone.

In several embodiments, the post and/or comments made by the socialnetwork friends of the user 112A are assigned a different weight by aprocessor than that assigned to the user 112A. For example, when asocial network friend of the user 112A posts a comment indicating thatthe user 112A will or will not achieve the total activity level withinthe remainder time period, the comment is assigned a lower weight thanthat assigned to a post by the user 112A that the user 112A will or willnot achieve the total activity level in the remaining time period.

In some embodiments, the post and/or comments made by the social networkfriends of the user 112A are assigned a different weight by a processorthan that assigned to the user 112A based on whether the other users aresimilar to the user 112A. For example, it is determined by a processorwhether the other users have similar demographics or dissimilardemographics as that of the user 112A. Upon determining that the otherusers are similar to the user 112A, the posts and/or comments made bythe other users regarding achievement of the total activity level withinthe remaining time period are provided a higher weight than thatprovided when the other users are dissimilar to the user 112A.

The demographics of the user 112A and the other users are accessed fromthe social network database by the processor of a monitoring device, theprocessor of the computing device 166, or the processor of the server228.

In various embodiments, the total activity level is calculated by aprocessor based on an addition of activity levels of the first activityperformed by the user 112A until the beginning of the remainder timeperiod and a statistical value, e.g., mean, median, etc., of theactivity levels. For example, an average of the activity levels of thefirst activity is calculated and the average activity level ismultiplied by a time element of the remaining time period in achievingthe milestone. The total activity level is a product of the averageactivity level and a number of time elements in the remaining timeperiod.

In some embodiments, instead of performing the operation 808 upondetermining that there is the reduced likelihood of achieving themilestone, a processor changes the milestone to a new milestone that canbe achieved by the user 112A. The processor may be the processor of amonitoring device, the processor of the computing device 166, or theprocessor of the server 228. On the other hand, upon determining thatthere is a likelihood of achieving the milestone and that the milestoneis achieved, the processor performs the operation 806.

In various embodiments, the action/location database includes thehistorical database.

FIG. 10A is a flowchart of an embodiment of a method 801 forrecommending a location or an activity to the user 112A to achieve amilestone. The recommendation of FIG. 10A is based on an activityperformed by the user 112A at one or more locations. The method 801 isexecuted by the processor of a monitoring device, the processor of theserver 228, or the processor of the computing device 166.

The method 801 includes an operation 803 of receiving a goal, e.g., thegoal G1, the goal G2, the goal G3, or the goal G4, associated with afirst activity of the user 112A, or a first location of a monitoringdevice, or a computer social network of the user, or an advertiser, or acombination thereof. As an example, the first activity is identifiedwith the activity identifier 132D (FIG. 11B) or the activity identifier132B (FIG. 11B). As another example, the first location is identifiedwith the location identifier 132A (FIG. 11B), the location identifier132B (FIG. 11B), or the location identifier 132C (FIG. 11B).

In some embodiments, each goal or each milestone is tracked monthly by aprocessor to determine whether the goal or milestone is achieved.Examples of a goal or a milestone include “I want to go to the gym atleast two times a week”, or “I want to play golf three times a month”,or “I want to achieve an activity level at work of at least 100 stepsper hour”, or “I want to stay at work less than 9 hours”, or “I want toget up before 7 AM each work day”, or “I want to walk at least 20minutes per week”, or “I want to commute for less than 30 minutes eachway to work”, or “I want to train for a half marathon”, or “I want totrain to go on a 50 mile backpack trip”, or “I want to train for acycling race”, or “I want to lose 10 pounds” or “I want to go to thegolf course at least once per month”, or “I want to go on a 30 minutewalk at least once a week”, or “I want to go on a run for at least 20minutes per week”, etc.

Examples of the computer social network include a social network that isused to post messages and comment on the messages. The social network isaccessed by multiple users via corresponding social network accounts tocommunicate with each other.

The goal is received in the operation 803 via the user interface of amonitoring device or via the input device of the computing device 166.In embodiments in which the goal is received in the operation 803 by theserver 228, the goal is received from a communication device of amonitoring device and the network 176 by the NIC of the server 228.Moreover, in these embodiments, the goal may otherwise be received fromthe NIC of the computing device 166 and the network 176 by the NIC ofthe server 228.

In some embodiments, the goal is associated with the first activity whenthe user 112A tries to achieve the goal using the first activity. Forexample, the user 112A tries to achieve the goal by walking 10 miles aday. As another example, the user tries to achieve the goal by doingyoga for 20 minutes.

Examples of a goal include losing an amount of weight, or achieving anactivity level, or performing an activity, or performing an activity ata location, or achieving an activity level at a location, etc.

In several embodiments, the goal is associated with the first locationwhen the user 112A tries to achieve the goal at the first location. Forexample, the user 112A tries to achieve the goal by walking at a park.As another example, the user 112A tries to achieve the goal by doingyoga at a gym.

In several embodiments, the goal is associated with the social networkwhen the goal is set using the social network. For example, socialnetwork friends compete with each other to achieve a goal. In thisexample, the social network friends post or comment on the socialnetwork that they would like to achieve the goal. To illustrate, a goalmay be that “I want to talk more steps than John Smith”, who is a socialnetwork friend of the user 112A. In this illustration, the goal isrelative to another user named John Smith. In these embodiments, thesocial network is linked with the processor of the server 228, theprocessor of the computer 166, or the processor of a monitoring device.The processor of the server 228, the processor of the computer 166, orthe processor of a monitoring device, with a permission of the user 112Aextracts posts and/comments made by the user 112A in his/her socialnetwork account. In some embodiments, the social network account of theuser 112A is linked to the user account 174.

In some embodiments, a goal is associated with the advertiser when theadvertiser provides the goal to promote its product/services or when thegoal is provided on behalf of the advertiser. For example, a gym owneradvertises that the user 112A will be able to lose 10 pounds in a monthby using its gym. As another example, a food product owner pitches thatthe user 112A will be able to lose weight by eating its milkshakes andrunning for a number of miles each day for a month. As yet anotherexample, an advertiser sponsors a competition between users to achieve agoal or a milestone. As another example, a fitness company, which is anexample of an advertiser, creates training programs, which includemilestones or goals, and provides prizes, e.g., awards, etc., when themilestones or goals are achieved. As yet another example, an entitydefines an ordered list of locations that users may go to within anamount of time while walking or running. When they reach a location,each user is given a clue of the next location. In this example, eachlocation reached is a milestone achieved. In some embodiments, when auser reaches a location, the user checks into a social network accountof a social network service to indicate that the user has reached thelocation. In various embodiments, the location reached by the user isdetermined based on geo-location data and the geo-location-locationdatabase. As yet another example, an advertiser promotes a public eventin an area in which the user 112A is located.

Examples of an advertiser include an advertising entity or anadvertising person. An advertiser promotes a product or a service.

The method 801 further includes an operation 805 of determining whethera milestone to achieve the goal is reached. For example, it isdetermined whether an amount of the first activity is performed by theuser 112A over a period of time allocated to achieve a milestone. Toillustrate, it is determined whether an activity level is achieved bythe user 112A over a period of time allocated to achieve a milestone. Insome embodiments, a sum of activity levels is calculated over the periodof time to determine whether a total of the sum is at a milestone.

Examples of the milestone include a milestone 1 (FIGS. 11A, 11B, 11C,11D), a milestone 2 (FIGS. 11A, 11B, 11C, 11D), and a milestone 3 (FIG.11D). Examples of an amount of the first activity performed by the user112A over a period of time include an amount A1 (FIG. 11A), an amount A2(FIG. 11B), an amount A3 (FIG. 11C), and an amount A4 (FIG. 11D).

Upon determining that the milestone to achieve the goal is not reached,an operation 808 of the method 801 is performed to help the user 112Aachieve a milestone. In the operation 808, a recommendation of a secondlocation to be visited by the user, an amount of a second activity to beperformed by the user, or a combination of the second activity and thesecond location is generated is performed to help the user 112A achievea milestone.

Examples of the amount of the second activity include an activity levelof the second activity over a remainder of a period of time. Toillustrate, the amount of second activity includes a number of steps tobe walked or ran by the user 112A over a remainder of a period of time,a number of calories to be burned by the user 112A over a remainder of aperiod of time, a number of stairs to be climbed or descended by theuser 112A over a remainder of a period of time, a number of sit-ups tobe done by the user 112A over a remainder of a period of time, or anumber of push-ups to be done by the user 112A over a remainder of aperiod of time, etc. In these examples, the remainder of a period oftime is any remaining time allocated to achieve a milestone. Theremaining time is a portion of time allocated to achieve a milestoneafter determining that the user 112A will not achieve the milestone byperforming the first activity.

In some embodiments, the second location is determined based on thefirst activity and a distance between the first location and the secondlocation. For example, it is determined whether the user 112A can walkin a park instead of at work and whether the park facilitates walking.In this example, information regarding whether the park facilitateswalking is retrieved from a website that displays the information. Theinformation regarding the park is requested from the website by theserver 228 or by the processor of a monitoring device or by theprocessor of the computing device 166. In this example, a distancebetween the work place and the park is calculated based on one or moregeo-locations of the park and one or more geo-locations of the workplace. As another example, it is determined whether the user 112A can doyoga in a gym instead of at home of the user 112A. In this example, adistance between the gym and the home is calculated based on one or moregeo-locations of the gym and one or more geo-locations of the home.

In various embodiments, the second activity is determined based on adistance between the first location and the second location. Forexample, it is determined whether there is a park close to a home of theuser 112A and whether the park allows running or swimming. In thisexample, information regarding whether the park facilitates running orswimming is retrieved from a website that displays the information. Theinformation regarding the park is requested from the website by theserver 228 or by the processor of a monitoring device or by theprocessor of the computing device 166. The closeness of the park to thehome is determined based on a distance between one of more geo-locationsof the home and one or more geo-locations of the park. In this example,the second activity recommended to the user 112A is running or swimmingand the first activity performed by the user 112A is walking. As anotherexample, it is determined whether there is a park close to a golf coursebased on a distance between the park and the golf course. The user 112Aplays golf at the golf course and the user 112A is recommended walking,running, or swimming at the park. In this example, golfing is an exampleof the first activity and walking, running, or swimming is an example ofthe second activity. In this example, information regarding whether thepark facilitates running or swimming or walking is retrieved from awebsite that displays the information. The information regarding thepark is requested from the website by the server 228 or by the processorof a monitoring device or by the processor of the computing device 166.As yet another example, it is determined that there is a yoga studio twoblocks away from a work place. As another example, it is determined thatthere is a park three blocks away from the home of the user 112A.

Examples of the recommendation to achieve a milestone include arecommendation R1 (FIG. 11A), a recommendation R2 (FIG. 11C), arecommendation R3 (FIG. 11D), a recommendation R4 (FIG. 12), arecommendation R5 (FIG. 13), a recommendation R6 (FIG. 13), and arecommendation R8 (FIG. 15).

The second location and/or an amount of a second activity to beperformed by the user 112A is recommended to the user 112A to achievethe milestone. For example, it is determined that by running at a parkinstead of walking at the park, the user 112A will achieve a milestoneof 20,000 steps in a day. As another example, it is determined that bydoing yoga at a gym for 20 minutes each day for a week instead of athome for the same amount of time each day of the week, the user 112Awill achieve a milestone of burning a number of calories in a week.

In some embodiments, the second activity is the same as the firstactivity. For example, both the first and second activities are walking.As another example, both the first and second activities are doing yoga.

In various embodiments, the second activity is different from the firstactivity. For example, the second activity is running and the firstactivity is walking. As another example, the second activity is playinga sport and the first activity is yoga.

In several embodiments, the first location is the same as the secondlocation. For example, each of the first and second location is a homeof the user 112A. As another example, each of the first and secondlocation is a gym or a sports club. As another example, each of thefirst and second location is work place of the user 112A.

In some embodiments, the first location is different from the secondlocation. For example, the first location is a home of the user 112A andthe second location is a gym. As another example, the first location isa home of the user 112A and the second location is a home of anotheruser. As yet another example, the first location is a gym located at anaddress and the second location is another gym located at anotheraddress.

In several embodiments, the operation of determining whether themilestone is reached is performed based on calorie information, which isgenerated based on a location of an eating place at which the user 112Ahas consumed food or drinks. For example, it is determined that the user112A has consumed an amount of calories when the user 112A visited asandwich place. The amount of calories consumed by the user 112A at theeating place takes the user 112A away from a milestone or brings theuser 112A closer to the milestone. In this example, the milestone ismeasured in terms of calories.

In some embodiments, the amount of calories of food eaten or liquidsdrank by the user 112A at the eating place are received from the user112A via the user interface of a monitoring device or the input deviceof the computing device 166. In several embodiments, the amount ofcalories of food eaten or liquids drank by the user 112A at the eatingplace is retrieved from a calorie information database by a processorvia the network 176. The processor may be the processor of the server228, the processor of a monitoring device, or the processor of computingdevice 228. The calorie information database is generated by the eatingplace and stored on the network 176 or within the memory device of theserver 228.

Examples of the eating place include a restaurant, a sandwich shop, acoffee shop, a bar, etc.

In various embodiments, the operation 808 of recommending the secondlocation includes adding a graphical element representing that thesecond location provides healthy food. An example of the graphicalelement representing that the second location provides healthy food is agraphical element 816 (FIG. 12). It is recommended that the user 112Acan eat at an eating place having food having calorie information withinthe graphical element 816 and eating at the place will not derail theuser 112A from achieving his/her milestone.

In various embodiments, the operation 808 of recommending the secondlocation includes adding a graphical element representing that thesecond location provides unhealthy food. It is recommended that the user112A not eat at the unhealthy eating place having food with calorieinformation displayed within a graphical element and eating at the placewill derail the user 112A from achieving his/her milestone.

In several embodiments, when a number of calories in food and/or drinksprovided by an eating place does not exceed a caloric limit, the eatingplace is designated as healthy by a processor. On the other hand, whenthe number of calories is at least equal to the caloric limit, theeating place is considered unhealthy. A processor calculates a number ofcalories in food and/or drinks served by an eating place and determineswhether the eating place is healthy. The processor may be the processorof a monitoring device, the processor of the computing device 166, orthe processor of the server 228.

The method 801 includes an operation 806 of providing acomputer-generated award to the user account 174 of the user upondetermining in the operation 805 that the milestone is reached. Anexample of the computer-generated award includes the badge B1. Otherexamples of the computer-generated award include virtual coins for usein an online game, or coupons for receiving discounts on a product orservice, or points in an online game, or a combination thereof.

FIG. 10B is a diagram of an embodiment of a flowchart of a method 830for recommending a location or an activity to the user 112A to achieve amilestone. The recommendation of FIG. 10B is based on one or moreactivities performed by the user 112A at one or more locations. Themethod 830 is the same as the method 801 (FIG. 10A) except in the method830 includes an operation 832 of setting the goal.

The operation 832 is performed by the processor of a monitoring device,or by the processor of the server 228, or by the processor of thecomputing device 166.

In some embodiments, the setting of the goal is performed based on ahistory of the user 112A. For example, the history of the user 112A mayindicate that the user 112A cannot run or walk. In this example, thehistory of the user 112A indicates that the user 112A is injured in anaccident. Moreover, in this example, the history of the user 112A isextracted from posts and/or comments made by the user 112A and/or hissocial network friends. In this example, the goal is set to doing yogainstead of walking or running for an amount of time. In variousembodiments, the setting of the goal is based on a target weight torecommend to the user 112A and a current weight of the user 112A. Thetarget weight is does not exceed a pre-determined weight.

FIG. 10C is a flowchart of an embodiment of a method 824 forrecommending a location or an activity to the user 112A to achieve agoal. The recommendation of FIG. 10C is based on one or more activitiesperformed by the user 112A at one or more locations. The method 824 isexecuted by the processor of a monitoring device, the processor of theserver 228, or the processor of the computing device 166.

The method 824 includes the operation 803.

The method 824 further includes an operation 820 of determining whetherthe goal is achieved. For example, it is determined whether an amount ofthe first activity is performed by the user 112A over an amount of timeallocated to achieve the goal. To illustrate, it is determined whetheran activity level is achieved by the user 112A over an amount of timeallocated to achieve the goal. In some embodiments, a sum of activitylevels is calculated over an amount of time to determine whether a totalof the sum is at a goal.

Upon determining that the goal is not reached, an operation 822 of themethod 824 is performed to help the user 112A achieve the goal. In theoperation 822, a recommendation of the second location to be visited bythe user, an amount of a second activity to be performed by the user, ora combination of the second location and the second activity isgenerated to help the user 112A achieve a goal.

Examples of the amount of the second activity include an activity levelof the second activity over a remainder of an amount of time. Toillustrate, the amount of second activity includes a number of steps tobe walked or ran by the user 112A over a remainder of an amount of time,a number of calories to be burned by the user 112A over a remainder ofan amount of time, a number of stairs to be climbed or descended by theuser 112A over a remainder of an amount of time, a number of sit-ups tobe done by the user 112A over a remainder of an amount of time, or anumber of push-ups to be done by the user 112A over a remainder of anamount of time, etc. In these examples, the remainder of an amount oftime is any remaining time allocated to achieve a goal. The remainingtime is a portion of time allocated to achieve a goal after determiningthat the user 112A will not achieve the goal by performing the firstactivity.

Examples of the recommendation to achieve a goal include therecommendation R7 and the recommendation R9.

The second location and/or an amount of a second activity to beperformed by the user 112A is recommended to the user 112A in theoperation 822 to achieve the goal. For example, it is determined that byrunning at a park instead of walking at the park for a remaining amountof time in a month, the user 112A will achieve a goal of 360,000 stepsin the month. As another example, it is determined that by doing yoga ata gym for 20 minutes each day for a remainder of a month instead of athome for the same amount of time each day of the remainder of the month,the user 112A will achieve a goal of burning a number of calories in themonth.

In several embodiments, the operation 820 of determining whether thegoal is reached is performed based on calorie information, which isgenerated based on a location of an eating place at which the user 112Ahas consumed food. For example, it is determined that the user 112A hasconsumed an amount of calories when the user 112A visited a sandwichplace. The amount of calories consumed by the user 112A at the eatingplace takes the user 112A away from a goal or brings the user 112Acloser to the goal. In this example, the goal is measured in terms ofcalories.

The method 824 includes an operation 824 of providing acomputer-generated award to the user account 174 of the user upondetermining in the operation 820 that the goal is reached.

FIG. 10D is a flowchart of an embodiment of a method 834 forrecommending a location or an activity to the user 112A to achieve agoal. The recommendation of FIG. 10D is based on an activity performedby the user 112A at one or more locations. The method 834 is executed bythe processor of a monitoring device, the processor of the server 228,or the processor of the computing device 166. The method 834 includesthe operations 832, 820, 824, and 822.

FIG. 11A is a diagram of an embodiment of a GUI 902 for illustrating useof one or more milestones to achieve a goal and a recommendation toachieve a milestone. The GUI 902 is generated by the processor of amonitoring device, the processor of the server 228, or the processor ofthe computing device 166.

The GUI 902 includes the GUI 370 (FIG. 7A). The GUI 902 includes anevent region 904 that further includes the recommendation R1, whichindicates to “ADD S1 SWINGS TO ACHIEVE MILESTONE 1”.

The goal G1 includes milestones 1 and 2. The goal G1, the milestones 1and 2 of the goal G1, and the recommendation R1 are overlaid on theevent 126 ₄. In some embodiments, the goal G1, the milestones 1 and 2 ofthe goal G1, and the recommendation R1 are overlaid on any portion ofthe GUI 370 (FIG. 7A). In various embodiments, the goal G1, themilestones 1 and 2 of the goal G1, and the recommendation R1 areoverlaid below the event data 126 ₄ or below any other portion of theGUI 370 (FIG. 7A).

The goal G1 may be to achieve an activity level in a day or in a monthor in a year or in a number of years. The milestones 1 and 2 aremilestones to achieve the goal G1. The milestone 1 may be to achieve anactivity level in a portion of a day, a portion of a month, a portion ofyear, or a portion of a number of years.

The amount A1 is an amount of the first activity performed by the user112A during a time period. For example, the amount A1 is a sum ofactivity levels of an activity of golfing performed by the user 112Afrom a time between 8 AM and 9 AM until a time between 10 AM and 11 AMon Thursday, March 1. The amount A1 is not enough to achieve themilestone 1. The amount A1 is an example of the current performancemetric.

The recommendation R1 is a recommendation to the user account 174 toachieve the milestone 1. For example, the recommendation R1 is to add S1swings to a golf game of the user 112A for a remaining time period froma time between 10 AM and 11 AM to a time between 3 PM and 4 PM. A totaltime period from a time between 8 AM and 9 AM to a time between 3 PM and4 PM is allocated to achieve the milestone 1 of the goal G1.

FIG. 11B is a diagram of an embodiment of a GUI 906 to illustrateprovision of a computer-generated award to the user account 174 when amilestone is achieved. The GUI 906 is generated by the processor of amonitoring device, the processor of the server 228, or the processor ofthe computing device 166. The GUI 906 includes the GUI 370 (FIG. 7A).

The GUI 906 includes an event region 908 that further includes the badgeB1 that is provided to the user 112A upon achieving the milestone 1 ofthe goal G2. For example, when the amount A2 of activity is equal to themilestone 1, the badge B1 is awarded to the user account 174.

The badge B1 is provided with a comment 909, which indicates that “YOUACHIEVED MILESTONE 1. HERE IS A GOLF BADGE”. In some embodiments, theuser 112A selects the comment 909 via the user interface of a monitoringdevice or the input device of the computing device 166 to close thecomment 909. Once the comment 909 is closed, the badge B1 is displayedon the GUI 906. In some embodiments, the badge B1 is provided to theuser account 174 and displayed within the GUI 906 without the comment909.

The goal G2 includes a milestone 1 and a milestone 2. The goal G2, themilestones 1 and 2 of the goal G2, and the comment 909 are overlaid onthe event 126 ₄. In some embodiments, the goal G2, the milestones 1 and2 of the goal G2, and the comment 909 are overlaid on any portion of theGUI 370 (FIG. 7A). In various embodiments, the goal G2, the milestones 1and 2 of the goal G2, and the comment 909 are overlaid below the eventdata 126 ₄ or below any other portion of the GUI 370 (FIG. 7A).

FIG. 11C is a diagram of an embodiment of a GUI 910 to illustrate therecommendation R2 to achieve a milestone. The GUI 910 is generated bythe processor of a monitoring device, the processor of the server 228,or the processor of the computing device 166.

The GUI 910 includes the GUI 370 (FIG. 7A). The GUI 910 includes anevent region 912 that further includes the recommendation R2, whichindicates that “TO ACHIEVE MILESTONE 1, YOU CAN WALK/RUN AT A PARK ATADDRESS 1234 DRIVE, UNION CITY, Calif.”.

The goal G3, milestones 1 and 2 of the goal G3, and the recommendationR2 are overlaid on the event 126 ₄. In some embodiments, the goal G3,the milestones 1 and 2 of the goal G3, and the recommendation R2 areoverlaid on any portion of the GUI 370 (FIG. 7A). In variousembodiments, the goal G3, the milestones 1 and 2 of the goal G3, and therecommendation R2 are overlaid below the event data 126 ₄ or below anyother portion of the GUI 370 (FIG. 7A).

The milestone 1 of the goal G3 is not achieved with the amount A3 of anactivity level of an activity performed by the user 112A. For example,the user 112A played golf for a time period from 8 AM and 9 AM to a timebetween 10 AM and 11 AM and the user 112A did not achieve the milestone1 of the goal G3 at a golf course. When the user 112A walks/runs at thepark at the address 1234 instead of golfing for the remainder timeperiod from a time between 10 AM and 11 AM to a time between 3 PM and 4PM, the user 112A will achieve the milestone 1 of the goal G3. A totaltime period from a time between 8 AM and 9 AM to a time between 3 PM and4 PM is allocated to achieve the milestone 1 of the goal G3.

FIG. 11D is a diagram of an embodiment of a GUI 914 to illustrate thatthe user 112A may perform a different activity at a location than thatperformed by the user 112A so as to allow the user 112A to achieve amilestone. The GUI 914 is generated by the processor of a monitoringdevice, the processor of the server 228, or the processor of thecomputing device 166.

The GUI 914 includes the GUI 370 (FIG. 7A). The goal G4 includesmilestones 1 and 2.

The goal G4, the milestones 1 and 2 of the goal G4, and therecommendation R3 are overlaid on the event 126 ₄. In some embodiments,the goal G4, the milestones 1 and 2 of the goal G4, and therecommendation R3 are overlaid on any portion of the GUI 370 (FIG. 7A).In various embodiments, the goal G4, the milestones 1 and 2 of the goalG4, and the recommendation R3 are overlaid below the event data 126 ₄ orbelow any other portion of the GUI 370 (FIG. 7A).

It is determined that the amount A4 of an activity performed by the user112A at a location will not help the user 112A achieve the milestone 2of the goal G4. The amount A4 is performed for a time period from a timebetween 8 AM and 9 AM to a time between 11 AM and NOON. Upon determiningthat the amount A4 will not facilitate achieving the milestone 2 of thegoal G4, it is recommended to the user 112A in the recommendation R3that the user 112A may walk at a rate r1 on the same location that theuser 112A is performing the amount A4 of the activity. The walking is adifferent activity than golfing, which is performed by the user 112A forthe time period from a time between 8 AM and 9 AM to a time between 11AM and NOON. The activity of walking is recommended to be performed fora time period from a time between 11 AM and NOON to a time between 3 PMand 4 PM. A total time period from a time between 8 AM and 9 AM to atime between 3 PM and 4 PM is allocated to achieve the milestone 2 ofthe goal G4.

FIG. 12 is a diagram of an embodiment of a web page 924 to illustratethat the user 112A may achieve a milestone by visiting a location thatis close to another location of the user 112A and performing an activityat the location to be visited. The web page 924 has a web address 4. Theweb page 924 includes a GUI 920, which further includes the map 732 andan event region 922.

The GUI 920 is generated by the processor of a monitoring device, theprocessor of the server 228, or the processor of the computing device166.

The GUI 920 includes the GUI 716 (FIG. 7P). The goal G4 includesmilestones 1 and 2.

The goal G4, the milestones 1 and 2 of the goal G4, the recommendationR4, and the graphical element 816, are overlaid on the event region 730(FIG. 7P) to generate the event region 922. In some embodiments, the G4,the milestones 1 and 2 of the goal G4, the recommendation R4, and thegraphical element 816 are overlaid on any portion of the GUI 716 (FIG.7P). In various embodiments, the G4, the milestones 1 and 2 of the goalG4, the recommendation R4, and the graphical element 816 are overlaidbelow the event region 730 or below any other portion of the GUI 716(FIG. 7P).

It is determined that the user 112A will not be able to achieve amilestone 1 of a goal based on an activity of playing golf at a golfcourse in a time period from a time between 8 AM and 9 AM to a timebetween 11 AM and NOON. It is determined that a coffee shop is locatedclose to a golf course and that there is a walking area around thecoffee shop. It is recommended that the user 112A can eat at the coffeeshop and walk around the coffee shop to achieve the milestone 1 in aremaining time period from a time between 11 AM and NOON and a timebetween 2 PM and 3 PM.

Moreover, the graphical element 816 including calorie information aboutfood and liquids served at the coffee shop is displayed.

In some embodiments, a processor determines a location of a user or alocation to which the user intends to visit. For example, a processordetermines a first location that the user intends to visit based on acloseness of the first location and the user. To illustrate, upondetermining that a geo-location of the user is within a radius or adistance of the first location, the processor determines that the userintends to visit the first location. The processor retrieves a menu offood items at the first location and calories of the food items. Forexample, the processor queries a database of food items via the network.The database may be used to present a web page of an entity that servesthe food items or may be used to generate a website that is used toexpress opinions of users regarding the food items. The processordetermines whether the user will achieve his/her milestone if the userconsumes one or more of the food items based on the calories in the fooditems. For example, the processor determines based on activity levels ofthe user whether the user will achieve his/her milestone. Upondetermining that the user will not achieve his/her milestone, theprocessor generates a prompt on a display device to indicate to the userto avoid going to the first location and to visit a second location thatwill help the user achieve the milestone. In this example, the processormay determine whether the second location is nearby, e.g., within aradius of, within a pre-determined distance of, etc., of the firstlocation.

In some embodiments, the processor determines whether a location thatthe user exits is a place that serves food. Upon determining so, theprocessor generates a prompt to display to the user via a display deviceto identify food items that the user consumed at the location.

FIG. 13 is a diagram of an embodiment of a GUI 950 that illustrates arecommendation of performing a different activity without changing alocation of the user 112A. For example, when the recommendation R5indicating that “You should walk at home to achieve a milestone” isgenerated, the user 112A is at his home. As another example, when therecommendation R6 indicating that “You should walk on this golf courseto achieve a milestone” is generated, the user 112A is at the golfcourse.

The GUI 950 is generated by the processor of a monitoring device, theprocessor of the server 228, or the processor of the computing device166. The GUI 950 displays activities performed by the user 112A on March5^(th) and March 6^(th).

In some embodiments, one or more of the recommendations R5 and R6 areoverlaid on or under an event of a GUI described herein.

FIG. 14 is a diagram of an embodiment of a calendar GUI 952 and anothercalendar GUI 954 to illustrate the recommendation R7 to achieve a goaland to illustrate achievement of the goal by the user 112A. The calendarGUIs 952 and 954 are generated by the processor of a monitoring device,the processor of the server 228, or the processor of the computingdevice 166.

The recommendation R7 is overlaid on a calendar GUI to generate thecalendar GUI 952. In some embodiments, the recommendation R7 is overlaidbelow a calendar GUI to generate the calendar GUI 952. Therecommendation R7 includes that “You should wake up early to achieve yougoal of 10k steps”.

After the user 112A acts according to the recommendation R7, it isdetermined by a processor that the goal is achieved. For example, thecalendar GUI 954 indicates that the user 112A achieved his goal of 10ksteps by waking up at 7 AM.

FIG. 15 is a diagram illustrating the recommendation R8 to achieve amilestone. A motion of the user 112A is monitored by a monitoring deviceto determine that the user 112A is playing golf. It is also determinedbased on the motion that the user 112A swung n number of swings using agolf club. It is further determined based on a geo-location of the user112A whether the user 112A played 18 holes. This determination ofwhether the user 112A played 18 holes is made by the processor of amonitoring device, the processor of the server 228, or the processor ofthe computing device 166. The number of holes at a golf course isreceived from a golf course information database of a server of thenetwork 176. The number of holes is received by the server 228, thecomputing device 166, or a monitoring device.

Upon determining that the user 112A has not finished 18 holes and thatthe user 112A has not reached a milestone, it is recommended using therecommendation R8 that the user 112A play m more swings to achieve themilestone.

In some embodiments, the recommendation R8 is overlaid on or under eventdata of a GUI described herein.

FIG. 16 is a diagram of an embodiment of a GUI 990 that includes therecommendation R9 made by an advertiser. The GUI 990 includes activitylevels, location identifiers, and/or activity identifiers. When it isdetermined that the user 112A is at a location and has not achieved hismilestone, e.g., his activity level is low, his activity level has notreached a level, etc., the recommendation R9 is generated by or onbehalf of an advertiser, e.g., a gym owner. The GUI 990 is generated bythe processor of a monitoring device, the processor of the server 228,or the processor of the computing device 166.

FIG. 17 is a diagram of an embodiment of a GUI 992 that is presented toa user to receive demographic data regarding the user. Examples ofdemographic data include age, gender, residence, occupation, date ofbirth, or a combination thereof, etc. The GUI 992 is generated by theprocessor of a monitoring device, the processor of the server 228, orthe processor of the computing device 166. The demographic data isreceived from a user via the user interface of a monitoring device orthe input device of the computing device 166.

A recommendation is generated based on the demographic data of a user.For example, upon receiving a selection from a user that the user is astay-at-home mom, the user is not provided with a recommendation ofperforming an activity at work. As another example, upon receiving aselection from a user that the user is a student, the user is notprovided with a recommendation of performing an activity at work.

In some embodiments, a goal includes any number of milestones.

In some embodiments, functions or methods or operations described hereinas being performed by a processor of a device are performed by one ormore processors of the device. For example, a function of displaying aGUI is performed by a GPU (not shown) of the monitoring device 108Ainstead of by the processor 234 (FIG. 3A).

In a number of embodiments, all GUIs, described herein, are accessed bythe user 112A when the user 112A accesses the user account 174 (FIG.2A).

In some embodiments, all GUIs, described herein, are displayed on adisplay device of the monitoring device or on the display device of thecomputing device 166. For example, a GUI is generated by the processorof a monitoring device to be displayed on the display device of themonitoring device or on the display device of the computing device 166.In this example, GUI data used to display the GUI is sent from acommunication device of the monitoring device to a communication deviceof the computing device for display on the computing device. As anotherexample, a GUI is generated by the processor of the computing device 166to be displayed on the display device of the computing device 166 or onthe display device of a monitoring device. In this example, GUI dataused to display the GUI is sent from a communication device of thecomputing device 166 to a communication device of a monitoring devicefor display on the monitoring device.

In several embodiments, a recommendation is generated and sent to anemail account of the user 112A, or to the social network account of theuser 112A, or to the user account 174. The sending of the recommendationto the email account is done by the NIC of the server 228 to an emailserver at which the email account is stored. The recommendation isdisplayed within an email to the user 112A. For example, therecommendation is sent from a NIC of the email server to the NIC of thecomputing device 166 for display on the display device of the computingdevice 166 within an email. In this example, the recommendation may beforwarded from a communication device of the computing device 166 to acommunication device of a monitoring device to be displayed within anemail that is displayed on the display device of the monitoring device.As another example, the recommendation is sent from the NIC of the emailserver to a communication device of a monitoring device for displaywithin an email that is shown on the display device of the monitoringdevice.

Similarly, the sending of the recommendation to the social networkaccount is done by the NIC of the server 228 to a social network serverthat stores the social network account. The recommendation is displayedwithin a representation of the social network account to the user 112A.For example, the recommendation is sent from a NIC of the social networkserver to the NIC of the computing device 166 for display on the displaydevice of the computing device 166 within the representation of thesocial network account. In this example, the recommendation may beforwarded from a communication device of the computing device 166 to acommunication device of a monitoring device to be displayed within arepresentation, of the social network account, that is displayed on thedisplay device of the monitoring device. As another example, therecommendation is sent from the NIC of the social network server to acommunication device of a monitoring device for display within arepresentation of the social network account on the display device ofthe monitoring device.

It should be noted that in some embodiments, any recommendationgenerated by the server 228 is sent via the network 176 to the computingdevice for display on the display device of the computing device 166 oris sent via the network 176 to a monitoring device for display on thedisplay device of a monitoring device. Moreover, it is noted that invarious embodiments, a recommendation generated by the computing device166 may be sent to a monitoring device for display on the display deviceof the monitoring device.

In various embodiments, a web page is a GUI.

In some embodiments, a processor applies adaptive learning of locations.For example, a processor determines that a user is at a location and/orachieves an activity level of an activity at the location for a numberof times greater than a pre-determined number. The processor furtherdetermines a range of times at which the user is at the location for thenumber of times and/or achieves the activity level at the location. Whenthe user visits the location on a day after the processor determines therange of times, the processor determines whether a time at which theuser visits the location falls within the range of times. Upondetermining that the time at which the user visits the location at atime that falls within the range of times, the processor determines thatthe user is at the location and/or will achieve the activity level atthe location.

In several embodiments, a processor applies refined learning of locationand size. For example, a processor determines that the user 112A visitsan inside the user's home and determines that one or more geo-locationswithin the inside of the home corresponds to the home. In this example,the processor determines that the one or more geo-locations within theinside of the home corresponds to the home based on thegeo-location-location database or based on a selection received from theuser indicating that the geo-locations correspond to the home. In thisexample, a processor determines that the user 112A visits a backyard ofthe user's home and determines that one or more geo-locations of thebackyard of the home correspond to the home. In this example, theprocessor determines that one or more geo-locations of the backyardcorresponds to the home based on the geo-location-location database orbased on a selection received from the user indicating that thegeo-locations correspond to the home. When the user visits ageo-location within the backyard or the inside of the home for a nexttime, the processor determines that the user is at his/her home. Itshould be noted that although home is used as an example, in someembodiments, other locations, e.g., a gym, a work place, a golf course,a race track, etc., may be used.

In several embodiments, a processor determines a favorite route of auser based on a number of times the user follows the route. For example,a processor determines that a user follows a route for greater than apre-determined number of times. In this example, the processordetermines that the route is a favorite route of the user. In thisexample, the processor determines data associate with the route, e.g., astatistical amount of time taken to complete the route, or a locationclose to the route, or a destination of the route, or a combinationthereof, etc. In some embodiments, the processor determines thedestination of the route from a maps service or from thegeo-location-location database. Examples of the statistical amount oftime taken to complete the route include an average amount of time tocomplete the route, a maximum amount of time to complete the route, aminimum amount of time taken to complete the route, etc. In thisexample, the processor labels, within a GUI, the route with the dataassociated with the route. To illustrate, the processor labels a routeas “walk to a train” instead of “walk”. As another illustration, theprocessor labels a route as “morning walk to work” instead of “walk”. Asanother illustration, the processor labels a route as “3 mile run downCedar street” instead of “run”. As another illustration, the processorlabels a route as “6 mile beach run” instead of “run”. Examples of theroute include a dog walking route, a commute to work route, a runningroute, a route to a bus station, a route to a train station, a route towork, a route to home, a route to a friend's home, etc.

In some embodiments, a processor quantifies an emotional response when auser is responsive to a piece of entertainment. The emotional responseincludes a combination of the HRV and/or the GSR. Based on the emotionalresponse, the processor assigns a rating to the piece of entertainment.For example, when the HRV and/or the GSR indicate to the processor thatthe user is sleeping during a movie, the processor assigns a low ratingto the movie. On the other hand, when the HRV and/or the GSR indicate tothe processor that the user is excited during the movie, the processorassigns a high rating to the movie. Based on the HRV and/or the GSR, theprocessor determines a type of the piece of entertainment that the userlikes. In some embodiments, the processor prompts a user to provide therating. The piece of entertainment may be a movie, an opera, a ballet, aconcert, a song, a multimedia presentation, a television show, news,etc. Examples of a type of the piece of entertainment include a horrorpiece, an action piece, a drama piece, a sad piece, a comedy piece, etc.

In various embodiments, a processor determines that a user is at alocation at which the piece of entertainment is presented, e.g.,publicly displayed, shown, etc., and displays within a GUI that includesevent data information regarding the location. For example, a processordetermines that a user is at a movie theater and populates a GUI withshow times of movies at the theater. The show times of the movies areobtained from a website or a database that is used to present the showtimes. Other examples of information regarding the location includevideo games available at a theater, types of food available at aconcert, etc.

In various embodiments, a processor determines motion and locationfeatures from users to build a network database. For example, theprocessor determines that a user performs an activity at a location fora number of times and performs a motion signature that identifies theactivity for the number of times. The motion signature is a motion of auser that is substantially repeated over a time period. For example, afirst swimming motion when the user is at a swimming pool in a gym isperformed on day 1 and a second swimming motion when the user is at theswimming pool at the gym is performed on day 2. The first and secondmotions are within a standard deviation. When the user visits, e.g.,enters, etc., the location at another time, e.g., day 3, etc., theprocessor determines that the user is going to perform the same activitythat the user has performed for the number of times. For example, theprocessor determines based on the motion signature and the locationvisited for the number of times as soon as the user enters a gym thatthe user will swim at the gym. As another example, the processordetermines that the user will do yoga at a yoga place based on themotion signature and the location visited for the number of times.

It should be noted that in some embodiments, any method or function oroperation that is described herein as being performed by the processor226 of the monitoring device 108A (FIG. 3A) or by the processor 234 ofthe computing device 166 (FIG. 5) may be performed by the processor 302(FIG. 3B) of the monitoring device 108B or by the processor 190 (FIG.2A) of the server 228.

In several embodiments, a milestone is a goal. In one embodiment, anamount of time is the same as a time period. It should be understoodthat the various embodiments may be combined to define specificcombination embodiments, consistent with the teachings defined herein.

Embodiments described in the present disclosure may be practiced withvarious computer system configurations including hand-held devices,microprocessor systems, microprocessor-based or programmable consumerelectronics, minicomputers, mainframe computers and the like. Severalembodiments described in the present disclosure can also be practiced indistributed computing environments where tasks are performed by remoteprocessing devices that are linked through a wire-based or wirelessnetwork.

With the above embodiments in mind, it should be understood that anumber of embodiments described in the present disclosure can employvarious computer-implemented operations involving data stored incomputer systems. These operations are those requiring physicalmanipulation of physical quantities. Any of the operations describedherein that form part of various embodiments described in the presentdisclosure are useful machine operations. Several embodiments describedin the present disclosure also relates to a device or an apparatus forperforming these operations. The apparatus can be specially constructedfor a purpose, or the apparatus can be a computer selectively activatedor configured by a computer program stored in the computer. Inparticular, various machines can be used with computer programs writtenin accordance with the teachings herein, or it may be more convenient toconstruct a more specialized apparatus to perform the requiredoperations.

Various embodiments described in the present disclosure can also beembodied as computer-readable code on a non-transitory computer-readablemedium. The computer-readable medium is any data storage device that canstore data, which can be thereafter be read by a computer system.Examples of the computer-readable medium include hard drives, networkattached storage (NAS), ROM, RAM, compact disc-ROMs (CD-ROMs),CD-recordables (CD-Rs), CD-rewritables (RWs), magnetic tapes and otheroptical and non-optical data storage devices. The computer-readablemedium can include computer-readable tangible medium distributed over anetwork-coupled computer system so that the computer-readable code isstored and executed in a distributed fashion.

Although the method operations were described in a specific order, itshould be understood that other housekeeping operations may be performedin between operations, or operations may be performed in an order otherthan that shown, or operations may be adjusted so that they occur atslightly different times, or may be distributed in a system which allowsthe occurrence of the processing operations at various intervalsassociated with the processing, as long as the processing of the overlayoperations are performed in the desired way. For example, the operations104 and 118 in FIG. 6A are performed simultaneously or the operation 118is performed before the operation 104. As another example, theoperations 202 and 204 of FIG. 6D are performed simultaneously or theoperation 204 is performed before performing the operation 202. As yetanother example, the operation 223 of FIG. 6F may be performed before,or after, or simultaneous with the performance of the operation 229.

Although the foregoing embodiments have been described in some detailfor purposes of clarity of understanding, it will be apparent thatcertain changes and modifications can be practiced within the scope ofthe appended claims. Accordingly, the present embodiments are to beconsidered as illustrative and not restrictive, and the variousembodiments described in the present disclosure is not to be limited tothe details given herein, but may be modified within the scope andequivalents of the appended claims.

What is claimed is:
 1. A method comprising: receiving a goal via a useraccount of a user; calculating a current performance metric of the userassociated with a first geo-location; accessing via a computer network adatabase of caloric intake information associated with food consumed bythe user; determining whether the user will achieve the goal byprocessing the current performance metric of the user and data thatincludes the caloric intake information; and generating a recommendationthat includes an activity and a second geo-location for performing theactivity based on the processing of the caloric intake information, thegoal, and the first geo-location.
 2. The method of claim 1, wherein theuser is performing an activity while at the first geo-location, whereinthe monitoring device includes a sensor for sensing metric data whilethe activity is being performed by the user, wherein the activity thatis recommended is different from the activity performed by the userwhile at the first geo-location.
 3. The method of claim 1, furthercomprising: receiving a username and password from the user; determiningwhether the username and password is authentic; and providing access tothe user account upon determining that the username and password isauthentic.
 4. The method of claim 1, wherein determining whether theuser will achieve the goal includes determining whether the user willburn a number of calories in an amount of time.
 5. The method of claim1, wherein at least one of the first geolocation or the secondgeo-location is collected by a computing device while the user iscarrying the computing device and wearing the monitoring device, whereinthe at least one of the first geolocation or the second geo-locationincludes a latitude and a longitude, or an altitude, or a combination ofthe longitude, the latitude, and the altitude.
 6. The method of claim 1,wherein the goal is set by a processor of a server.
 7. The method ofclaim 1, wherein the goal is received from a computing device via thecomputer network, wherein the goal is provided to the computing deviceby the user via the user account and an input device.
 8. The method ofclaim 1, wherein the monitoring device includes a wristwatch, or awristband, or a bracelet.
 9. The method of claim 1, wherein a name ofthe food consumed by the user is provided by the user to the useraccount via a display device of the monitoring device.
 10. The method ofclaim 1, further comprising: receiving via the user account a number ofcalories burned by the user, wherein the number of calories burned bythe user is measured by the monitoring device while the user isperforming the activity, wherein processing the data includes counting anumber of calories to be burned by the user within a remaining timeperiod for achieving the goal based on the caloric intake information,the number of calories burned by the user, and a total number ofcalories to be burned by the user for achieving the goal, whereindetermining whether the user will achieve the goal includes determiningwhether the user will burn the number of calories to be burned by theuser in the remaining time period.
 11. The method of claim 1, furthercomprising: accessing calories that will be burned by the user when theuser will perform the activity; and determining based on the caloriesthat will be burned by the user that the user will achieve the goal uponperforming the activity at the second geo-location.
 12. The method ofclaim 1, further comprising: accessing a database to determine whetherthe activity is allowed to be performed at the second geo-location,wherein generating the recommendation includes generating therecommendation upon determining that the activity is allowed to beperformed at the second geo-location.
 13. A method comprising: receivinga goal via a user account of a user; receiving activity data from amonitoring device regarding an activity performed by the user at a firstgeo-location; receiving the first geo-location associated with themonitoring device; calculating a current performance metric of the userassociated with the first geo-location based at least partly on theactivity data; accessing via a computer network a database to identify anumber associated with caloric intake by the user; determining whetherthe user will achieve the goal within an amount of time based on thenumber associated with the caloric intake and the current performancemetric of the user; determining from the first geo-location whether theuser is within a pre-determined distance from a second geo-location; andgenerating a recommendation to the user account of the secondgeo-location suitable for performing a recommended activity upondetermining that the user will not achieve the goal.
 14. The method ofclaim 13, wherein receiving the activity data includes receiving anumber of steps taken by the user during a day, wherein the number ofsteps for the day are counted by a sensor of the monitoring device whilethe user is performing the activity at the first geo-location.
 15. Themethod of claim 13, wherein the first geo-location includes a longitudeand a latitude of the monitoring device, wherein the longitude andlatitude are determined by the monitoring device by using signalscommunicated between the monitoring device and another device.
 16. Themethod of claim 13, wherein the monitoring device is configured toreceive a food item consumed by the user via an input device of themonitoring device, wherein the number associated with the caloric intakeby the user is identified from the database for the food item consumedby the user.
 17. The method of claim 13, wherein the goal includes athreshold number of calories, wherein the activity data includes anumber of calories burned by the user, wherein determining whether theuser will achieve the goal includes: counting the number of caloriesburned by the user and the number associated with the caloric intake bythe user; determining that the count exceeds the threshold number ofcalories.
 18. The method of claim 13, further comprising: accessingcalories that will be burned by the user when the user will perform therecommended activity; and determining based on the calories that will beburned by the user that the user will achieve the goal upon performingthe recommended activity at the second geo-location.
 19. The method ofclaim 13, wherein the monitoring device includes a wristwatch, or awristband, or a bracelet.
 20. The method of claim 13, furthercomprising: accessing a database to determine whether the recommendedactivity is allowed to be performed at the second geo-location, whereingenerating the recommendation is performed upon determining that therecommended activity is allowed to be performed at the secondgeo-location.